Miracle-dz/UniFAR-FTUs huggingface dataset:
Grassland Management Influences the Response of Soil Respiration to Drought

Increasing soil carbon stocks in agricultural grasslands has a strong potential to mitigate climate change. However, large uncertainties around the drivers of soil respiration hinder our ability to identify management practices that enhance soil carbon sequestration. In a context where more intense and prolonged droughts are predicted in many regions, it is critical to understand how different management practices will temper drought-induced carbon losses through soil respiration. In this study, we compared the impact of changing soil volumetric water content during a drought on soil respiration in permanent grasslands managed either as grazed by dairy cows or as a mowing regime. Across treatments, root biomass explained 43% of the variability in soil respiration (p < 0.0001). Moreover, analysis of the isotopic composition of CO2 emitted from the soil, roots, and root-free soil suggested that the autotrophic component largely dominated soil respiration. Soil respiration was positively correlated with soil water content (p = 0.03) only for the grazed treatment. Our results suggest that the effect of soil water content on soil respiration was attributable mainly to an effect on root and rhizosphere activity in the grazed treatment. We conclude that farm management practices can alter the relationship between soil respiration and soil water content.
Optimization of total phenolic contents, antioxidant, and in-vitro xanthine oxidase inhibitory activity of sunflower head

ABSTRACT Sunflower head (Helianthus annuus, Asteraceae) is a residual by-product generated during the production of sunflower seed oil and contains a considerable amount of bioactive components. The aim of the present study was to determine and optimize extraction conditions for total phenolic content (TPC), antioxidant activities (DPPH, ABTS and FRAP) and xanthine oxidase (XOD) inhibitory activity of SH. The solute solvent ratio showed a significant effect on yield, TPC, antioxidant activities and XOD inhibition. The Box–Behnken design (BBD) was employed for optimization of extraction parameters (yield, TPC and antioxidant activities). The statistical findings for optimized conditions reveal that the best extraction of SH was obtained with the following parameters: ethanol (54.5%), temperature (72.3°C) and time (138.8 min). This present study may help in the industrial extraction process; moreover, further deep studies are required to optimize sequential steps to increase the efficacy.
Predicting post-absorptive protein and amino acid metabolism

ABSTRACT Sustainable production of adequate quantities of food to support a growing human population is a worldwide goal. Under current feeding conditions in the United States, dairy cattle convert dietary nitrogen to milk nitrogen with 25% efficiency. The remaining 75% is excreted, which contributes to air and water quality problems and reduces economic performance of the industry. Efficiency could be improved to 29% if protein was given to just meet current NRC requirements. Additional improvements may be achievable, but only [. ]
Effect of cold stratification and gibberellic acid on in vitro germination ofActinidia argutaandActinidia chinensis

The effect of cold stratification (CS) and gibberellic acid (GA3) alone and in combination on in vitro germination of Actinidia arguta and Actinidia chinensis seeds was studied. Sterile seeds of the two plant species were stratified at 4°C for 28 and 42 days. Batches of stratified and non-stratified (control) seeds from both plant species were germinated on plant growth regulator-free Murashige and Skoog (MS) media and also on sterile filter paper bridges moistened with dH2O and GA3 concentrations of 500, 1000, 1500, 2000 and 2500 ppm. In the two plant species, seeds from the control and the CS treatments alone did not germinate on MS medium. However on filter paper bridges, seeds cold stratified for 28 days yielded only 8 and 20% germination percentage (GP) in A. arguta and A. chinensis, respectively, whereas CS for 42 days did not promote germination. In A. arguta, treatments of non-stratified seeds with GA3 resulted in 91% optimum GP at 1572 ppm GA3 and optimum 29 days mean germination time (MGT) at 1678 ppm GA3. In A. chinensis, 48% optimum GP and 24 days optimum MGT were achieved at 2225 and 2033 ppm GA3 concentrations, respectively. Cold stratification (28 days) followed by GA3 treatments of A. arguta resulted in optimum GP of 88% and 23 days optimum MGT at GA3 concentrations of 1435 and 1610 ppm, respectively. The same combined treatment of A. chinensis seeds yielded optimum GP of 80% and optimum 25 days MGT at GA3 concentrations of 1565 and 2050 ppm, respectively. In contrast, CS (42 days) followed by GA3 in A. arguta resulted in optimum GP of 99% and 27 days optimum MGT at GA3 concentrations of 1563 and 2120 ppm, respectively. Similar treatments in A. chinensis seeds yielded optimum GP of 45% and optimum 23 days MGT at GA3 of 998 and 1629 ppm, respectively. In conclusion, CS alone had little effect on germination, whereas CS (28 days) followed by GA3 significantly (p≤0.05) improved GP in both plant species. Treatments with GA3 alone and CS (42 days) followed by GA3 were more effective on germination of A. arguta than A. chinensis. Germinated seeds on moist filter paper can produce seedlings when sub-cultured on MS medium for seedling development.
Model interatomic potentials for Fe–Ni–Cr–Co–Al high-entropy alloys

A set of embedded atom model (EAM) interatomic potentials was developed to represent highly idealized face-centered cubic (FCC) mixtures of Fe–Ni–Cr–Co–Al at near-equiatomic compositions. Potential functions for the transition metals and their crossed interactions are taken from our previous work for Fe–Ni–Cr–Co–Cu [D. Farkas and A. Caro: J. Mater. Res. 33 (19), 3218–3225, 2018], while cross-pair interactions involving Al were developed using a mix of the component pair functions fitted to known intermetallic properties. The resulting heats of mixing of all binary equiatomic random FCC mixtures not containing Al is low, but significant short-range ordering appears in those containing Al, driven by a large atomic size difference. The potentials are utilized to predict the relative stability of FCC quinary mixtures, as well as ordered L1_2 and B2 phases as a function of Al content. These predictions are in qualitative agreement with experiments. This interatomic potential set is developed to resemble but not model precisely the properties of this complex system, aiming at providing a tool to explore the consequences of the addition of a large size-misfit component into a high entropy mixture that develops multiphase microstructures.
Increasing the Predictive Validity of Identity Fusion in Leading to Sacrifice by Considering the Extremity of the Situation

When it comes to doing something for your group, one would intuitively think that as sacrifices get more extreme, fewer individuals would be willing to make them. Are there, however, some people who are actually more likely to self-sacrifice in extreme than non-extreme situations? The current research aims at addressing this question by varying the extremity of the situation that is considered and examining how it affects the willingness to self-sacrifice. Identity fusion is a remarkably strong form of group alignment in which the boundary between personal and social identity becomes porous, producing a visceral feeling of oneness with a group (Gómez & Vázquez, 2015; Swann et al., 2009, 2012). The result of this fusion is a powerful feeling of connectedness to a particular group category in which both the personal and the social self are activated. In turn, this allows fused individuals to experience a high sense of personal agency (i.e., the capacity to initiate and control intentional behavior) as well as derive strength from group membership. Thus, highly fused individuals are likely to develop strong relational ties with the group (involving attachment to fellow group members) because those who belong to the group are valued by virtue of both their group membership and their distinctive personal qualities (Vázquez et al., 2017). One of the unique features of this relatively novel fusion construct is its ability to predict the endorsement of radical progroup behaviors including ultimate sacrifices and extreme outcomes. In the present research, we examine the ability of identity fusion to guide willingness to self-sacrifice as a function of a new variable: the extremity of the situation that is made salient.
Post-harvest characterization of strawberry hybrids obtained from the crossing between commercial cultivars

Abstract The lack of programs to improve the strawberry crop in Brazil has led to a growing increase in the use of seedlings imported from Chile, which leads to a certain dependence of imported material on the part of the producers and increases the production even more, since the producers have. This proves even more the need for the development of cultivars adapted to the local conditions of cultivation. In this sense, the aim was to evaluate the post-harvest of fruits of 15 hybrids of strawberry obtained from the cross between commercial cultivars, in order to select the materials with chemical quality superior to the cultivars most planted in Brazil. The contents of soluble solids, titratable acidity, ratio, vitamin C, anthocyanins and phenol were evaluated. The characterization of strawberry hybrids indicated that the RVFS 13-07, RVFS 13-24, RVCS 13-07, RVCS 13-10 and RVCA 13-08 materials stood out in post-harvest evaluations, with higher levels of functional compounds (vitamin C, anthocyanins and phenolics) and higher values of quality parameters (soluble solids, titratable acidity and ratio), important characteristics for the in natura consumption or for use by the industry. These hybrids were shown to be promising to continue the crop breeding program by demonstrating that they carried characteristics of interest for intraspecific crosses. The values obtained for the analyzed characteristics were higher than the values found in the literature for the cultivars most planted and consumed in Brazil and in the World, which demonstrates the efficiency in the selection process.
Landau levels, edge states, and gauge choice in 2D quantum dots

We examine the behavior of a charged particle in a two dimensional quantum dot in the presence of a magnetic field. Emphasis is placed on the high magnetic field regime. Compared to free space geometry, confinement in a dot geometry provides a more realistic system where edge effects arise naturally. It also serves to remove the otherwise infinite degeneracy due to the magnetic field; nonetheless, as described in this paper, additional ingredients are required to produce sensible results. We treat both circular and square geometries, and in the latter, we explicitly demonstrate the gauge invariance of the energy levels and wave function amplitudes. The characteristics of bulk states closely resemble those of free space states. For edge states, with sufficiently high quantum numbers, we achieve significant differences in the square and circular geometries. Both circular and square geometries are shown to exhibit level crossing phenomena, similar to parabolic dots, where the confining potential is a parabolic trap. Confinement effects on the probability current are also analyzed; it is the edge states that contribute non-zero current to the system. The results are achieved using straightforward matrix mechanics, in a manner that is accessible to novices in the field. On a more pedagogical note, we also provide a thorough review of the theory of single electron Landau levels in free space and illustrate how the introduction of surfaces naturally leads to a more physically transparent description of a charged particle in a magnetic field.
Etude des ADN glycosylases de la superfamille structurale Fpg/Nei par modélisation moléculaire, de nouvelles cibles thérapeutiques potentielles dans les stratégies anti-cancer

L’ADN, support de l’information genetique, est constamment altere par des agents physiques ou chimiques d’origines endogenes (metabolisme) et exogenes (UV, radiations ionisantes, produits chimiques) dont les effets sont genotoxiques. Ces modifications structurales deleteres de l’ADN sont eliminees par de nombreux mecanismes de reparation. Parmi eux, le systeme de reparation par excision de bases (BER) est initie par les ADN glycosylases qui reconnaissent et eliminent les bases endommagees. Dans certaines strategies anti-cancereuses, l’utilisation de la chimiotherapie et la radiotherapie ont pour but la destruction des cellules cancereuses en alterant leur ADN. Dans ce contexte, les ADN glycosylases reparent l’ADN des cellules traitees et induisent une resistance non desiree au traitement, faisant de ces enzymes des cibles therapeutiques interessantes. Le but de ces travaux est d’approfondir la comprehension des mecanismes de reparation des ADN glycosylases de la superfamille structurale Fpg/Nei grâce a la modelisation moleculaire et de pouvoir identifier et concevoir des inhibiteurs de ces enzymes. Les simulations de dynamique moleculaire (DM) nous ont permis d’etudier la « Lesion Capping Loop » (LCL) et de l’associer a la stabilisation de la base endommagee positionnee dans le site actif. Nous avons egalement etudie les chemins de sortie possibles de la base apres coupure par l’enzyme et l’implication de la boucle LCL dans ce phenomene grâce a des simulations de DM ciblee (TMD-1). De plus, les simulations de DM couplees a un protocole d’amarrage moleculaire « aveugle » nous ont permis d’identifier 2 sites de fixations possibles majoritaires pour des petites molecules potentiellement inhibitrices. Un de ces sites correspondant au site actif de hNEIL1 a fait l’objet d’un criblage virtuel d’une partie de la base de molecules Ambinter. Ceci nous a permis d’identifier des molecules potentiellement inhibitrices dont les effets seront prochainement testes in vitro dans l’equipe sur la proteine humaine hNeil1.
A comparative study of ECEC practitioners’ perceptions of children’s well-being and their roles in South Korea and Norway

ABSTRACT This comparative study investigated how early childhood education and care practitioners in South Korea and Norway perceive the concept of children’s well-being and their own roles in supporting and facilitating children’s well-being. Data were collected through online questionnaires from 198 practitioners and analysed utilising chi-square analyses. The results showed that South Korean practitioners perceived the cognitive and economic domains as more important than Norwegian practitioners. Meanwhile, the practitioners from Norway perceived the social domain as more important than South Korean practitioners. Norwegian practitioners perceived physical needs, need for affection, and enjoyment as more important than Korean practitioners. Norwegian practitioners also monitored every child’s well-being and more actively encouraged positive interactions and child-initiated activities. Meanwhile, Korean practitioners perceived the need for safety as important and believed that environments were not safe enough for children’s health and well-being. These findings suggest that the educational approaches and sociocultural contexts of the two countries influence children’s well-being.
Eskişehir Kentsel Büyüme Alanın Hücresel Otomat ve CA-Markov Zincirleri ile Analizi (1984-2056)

Kentsel buyume, sahip oldugu farkli dinamiklere bagli olarak zaman icerisinde mekansal kullanim degisikliklerine yol acmaktadir. Bu degisiklerin yol acabilecegi sorunlara karsi tedbirli olmak ve planlama yapabilmek icin gelecekteki kent alanin yayilimini tahmin etmek oldukca onemlidir. Bu amacla Eskisehir kentsel alani 1984-2020 tarihleri baz alinarak incelenmis, uygulanan CA-Markov analizi ile 2056 yilindaki kentsel buyume alani on gorulmustur. Calismanin sonuclarina gore hizli kentlesme sureci yasayan Eskisehir’de kentsel buyumenin gelecekte de devam edecegi tespit edilmistir. Ayrica buyumenin yonunun kuzeybati-guneydogu aksinda devam etmesi beklenmektedir. Calismanin bulgularinin Eskisehir icin yapilan bir kentsel buyume senaryosunda, basta kent plancilari olmak uzere, tum karar alicilara fayda saglamasi beklenmektedir.
A Comprehensive Study of Clustering Algorithms in Data Stream

:- Clustering algorithms have been developed as an excellent algorithms to precisely break down the massive volume of information produced by modern applications. Specifically, their primary objective is to classify information into bunches to such an extent that data points gathered in a similar group are comparable. There is a huge volume of information in the zone of grouping and there have been activities to classify them into different types of groups. In any case, the main challenge of any clustering algorithm is, understanding of data dimensions, interpretation, combination of related data and taking relevant decisions. The main objective of any clustering algorithm is to reduce the issues listed. This paper gives a brief overview of existing bunching algorithms both from a hypothetical and an experimental point of view. From a theoretical viewpoint, we built up a clustering algorithm depending on the primary properties of the data like Data Size, Speed, Time Complexity, Data type, Cluster Shape, Partition Accuracy. Then we test the huge data collected, by applying a suitable classification method. Bunching is most widely used technique to partition data spaces and discover patterns. The behavior of different clustering algorithms is estimated through various interior and outer validity measurements, steadiness, runtime, and adaptability tests. Furthermore, in this paper a comprehensive study of clustering algorithms is performed to help the users in choosing the appropriate algorithm based on user’s requirement.
Indoor Positioning Method Using WiFi RTT Based on LOS Identification and Range Calibration

WiFi-based indoor positioning methods have attracted extensive attention due to the wide installation of WiFi access points (APs). Recently, the WiFi standard was modified and introduced into a new two-way approach based on round trip time (RTT) measurement, which brings some changes for indoor positioning based on WiFi. In this work, we propose a WiFi RTT positioning method based on line of sight (LOS) identification and range calibration. Given the complexity of the indoor environment, we design a non-line of sight (NLOS) and LOS identification algorithm based on scenario recognition. The positioning scenario is recognized to assist NLOS and LOS distances identification, and gaussian process regression (GPR) is utilized to construct the scenario recognition model. Meanwhile, the calibration model for LOS distance is presented to correct the measuring distance and the scenario information is utilized to constrain the estimated position. When there is a positioning request, the positioning scenario is identified with the scenario recognition model, and LOS measuring distance is obtained based on the recognized scenario. The LOS range measurements are first calibrated and then utilized to estimate the position of the smartphone. Finally, the positioning scenario is used to constrain the estimation location to avoid it beyond the scenario. The experimental results show that the positioning effect of the proposed method is far better than that of the Least Squares (LS) algorithm, achieving a mean error (ME) of 0.862 m and root-mean-square error (RMSE) of 0.989 m.
Effect of IDT position parameters on SAW yarn tension sensor sensitivity

In this paper, the effect of the interdigital transducer (IDT) position parameters on the surface acoustic wave (SAW) yarn tension sensor sensitivity is investigated. The stress–strain characteristic of substrate was studied by the combination of finite element simulation and regression analysis method. According to this characteristic, the function relationship between the SAW yarn tension sensor sensitivity and the IDT position parameters was built using the regression analysis method. The monotonicity of the regression function was also given. On this basis, a novel sensitivity optimal scheme was proposed and solved by the quadratic programming method. Its solution demonstrates that the optimum sensitivity can be obtained when the IDT is 8.9 mm to the left side of the substrate and the IDT is 0.3 mm to the top edge of the substrate within a domain of the IDT position parameters. The SAW yarn tension sensor with corresponding IDT position parameters was fabricated to validate the correctness of the sensitivity optimal scheme. The measured results indicate that the SAW yarn tension sensor sensitivity can reach 813.69 Hz/g, which confirms that the novel scheme is effective.
Recursive Cluster Elimination based Rank Function (SVM-RCE-R) implemented in KNIME

In our earlier study, we proposed a novel feature selection approach, Recursive Cluster Elimination with Support Vector Machines (SVM-RCE) and implemented this approach in Matlab. Interest in this approach has grown over time and several researchers have incorporated SVM-RCE into their studies, resulting in a substantial number of scientific publications. This increased interest encouraged us to reconsider how feature selection, particularly in biological datasets, can benefit from considering the relationships of those genes in the selection process, this led to our development of SVM-RCE-R. SVM-RCE-R, further enhances the capabilities of SVM-RCE by the addition of a novel user specified ranking function. This ranking function enables the user to stipulate the weights of the accuracy, sensitivity, specificity, f-measure, area under the curve and the precision in the ranking function This flexibility allows the user to select for greater sensitivity or greater specificity as needed for a specific project. The usefulness of SVM-RCE-R is further supported by development of the maTE tool which uses a similar approach to identify microRNA (miRNA) targets. We have also now implemented the SVM-RCE-R algorithm in Knime in order to make it easier to applyThe use of SVM-RCE-R in Knime is simple and intuitive and allows researchers to immediately begin their analysis without having to consult an information technology specialist. The input for the Knime implemented tool is an EXCEL file (or text or CSV) with a simple structure and the output is also an EXCEL file. The Knime version also incorporates new features not available in SVM-RCE. The results show that the inclusion of the ranking function has a significant impact on the performance of SVM-RCE-R. Some of the clusters that achieve high scores for a specified ranking can also have high scores in other metrics.
A Mobility-Predict-based Forwarding Strategy in Vehicular Named Data Networks

Named data networking (NDN) is promising for Vehicular Ad hoc Networks (VANETs) owing to its data-centric communication paradigm. However, the existing forwarding strategies for vehicular named data networks (VNDN) cannot handle well the issues of high mobility and broadcast storm. In this paper, we propose a Mobility-Predict-based Forwarding Strategy (MPFS) to tackle these issues in VNDN. First, in order to solve the problem of outdated mobility information in the neighbor table, a lightweight but highly effective approach is proposed to predict the current position in MPFS. Then, the predicted mobility information of the vehicles in the neighbor table is applied to select the next-hop forwarder(s) in both directions (road direction and reverse road direction) of the consumer. Furthermore, the vehicle that is farthest from the current forwarder with a stable link is considered as the next-hop forwarder. Finally, extensive simulations are carried out to demonstrate that MPFS has a less number of Interest packets forwarded, while maintaining a higher ratio of satisfied Interest packets compared with the baseline forwarding strategies.