Miracle-dz/UniFAR-FTUs huggingface dataset:
Self-creation cosmology: A Review

Over 60 authors have worked on various versions of self-creation cosmology (SCC) since the original paper in 1982. These papers adapted the Brans Dicke theory to create mass out of the universe's self contained scalar, gravitational and matter fields. The most recent 2002 version of the theory was concordant with all previous standard tests of GR but was falsified by the Gravity Probe B geodetic precession experiment. Here the different versions of the theory are reviewed and it is noted that the 2002 theory not only reduces to the second 1982 theory when cast into a the 'true' form of the scalar field stress-energy tensor but also in that form it passes the GP-B test. Further experiments are able to resolve the SCC-GR degeneracy, one of which is briefly described. SCC may be able to explain some intriguing anomalies also, in the spherically symmetric One-Body problem, it transpires that the temporal Newtonian potential is three times larger than the spatial one. Cosmological solutions to the field equations, which have been published elsewhere, are extended to show that the cosmological density parameter Omega =1.
The Small Ras Superfamily GTPase Rho4 of the Maize Anthracnose Fungus Colletotrichum graminicola Is Required for β-1,3-glucan Synthesis, Cell Wall Integrity, and Full Virulence

Small Ras superfamily GTPases are highly conserved regulatory factors of fungal cell wall biosynthesis and morphogenesis. Previous experiments have shown that the Rho4-like protein of the maize anthracnose fungus Colletotrichum graminicola, formerly erroneously annotated as a Rho1 protein, physically interacts with the β-1,3-glucan synthase Gls1 (Lange et al., 2014; Curr. Genet. 60:343–350). Here, we show that Rho4 is required for β-1,3-glucan synthesis. Accordingly, Δrho4 strains formed distorted vegetative hyphae with swellings, and exhibited strongly reduced rates of hyphal growth and defects in asexual sporulation. Moreover, on host cuticles, conidia of Δrho4 strains formed long hyphae with hyphopodia, rather than short germ tubes with appressoria. Hyphopodia of Δrho4 strains exhibited penetration defects and often germinated laterally, indicative of cell wall weaknesses. In planta differentiated infection hyphae of Δrho4 strains were fringy, and anthracnose disease symptoms caused by these strains on intact and wounded maize leaf segments were significantly weaker than those caused by the WT strain. A retarded disease symptom development was confirmed by qPCR analyses. Collectively, we identified the Ras GTPase Rho4 as a new virulence factor of C. graminicola.
PSO-based optimized neural network PID control approach for a four wheeled omnidirectional mobile robot

The demand for automation using mobile robots has been increased dramatically in the last decade. Nowadays, mobile robots are used for various applications that are not attainable to humans. Omnidirectional mobile robots are one particular type of these mobile robots, which has been the center of attention for their maneuverability and ability to track complex trajectories with ease, unlike their differential type counterparts. However, one of the disadvantages of these robots is their complex dynamical model, which poses several challenges to their control approach. In this work, the modeling of a four-wheeled omnidirectional mobile robot is developed. Moreover, an intelligent Proportional Integral Derivative (PID) neural network control methodology is developed for trajectory tracking tasks, and Particle Swarm Optimization (PSO) algorithm is utilized to find optimized controller's weights. The simulation study is conducted using Simulink and Matlab package, and the results confirmed the accuracy of the proposed intelligent control method to perform trajectory tracking tasks.
High Stability PGC-EFA-DCM Demodulation Algorithm Integrated With a PID Module

Phase generated carrier (PGC) demodulation technology has been widely used in fiber-optic interferometric sensors while nonlinearity is always accompanying with the scheme. We propose a highly stable PGC demodulation algorithm combining internal modulation, ellipse fitting algorithm (EFA), phase modulation depth (C) self-calibration and differential-cross-multiplying (DCM). A low frequency triangular signal is added to the laser modulation, which ensures the effectiveness of the EFA under small signal condition. And the real-time C value is calculated by using the ellipse fitting parameters and calibrated to the optimal value of 2.63 rad by a closed loop proportion integration differentiation (PID) module. Furthermore, nonlinear distortions are suppressed by the EFA. Experimental results show that the signal-to-noise and distortion ratio (SINAD) and total harmonic distortion (THD) of the proposed scheme are improved by 13.61 dB and 0.12% than the conventional PGC-DCM algorithm. The standard deviation of C decreased from 0.0178 rad to 0.0058 rad in 1024 seconds. The dynamic range, linearity and phase resolution of the system reach 117.73 dB @ 1 kHz, 99.99% and 4.6 μrad/√Hz, respectively.
Dietary Ground Flaxseed Increases Serum Alpha-Linolenic Acid Concentrations in Adult Cats

Simple Summary The use of flaxseed in complete pet foods as a source of omega-3 fatty acids, and in particular alpha-linolenic acid, has been studied extensively in dogs. However, to date, no scientific published literature exists on the impacts of feeding whole ground flaxseed as an ingredient in cat food on nutrient digestibility, fatty acid bioavailability, and overall health in cats. In addition, dietary flaxseed inclusion has been challenged as providing little nutritional value for cats by not changing serum fatty acid levels and lowering nutrient digestibility. Therefore, the objective of this study was to directly evaluate the effects of adding ground flaxseed to dry cat food on fatty acid bioavailability, stool consistency, nutrient digestibility, and overall health in adult cats. These results clearly exhibit that a flaxseed-supplemented diet resulted in no changes in stool quality or nutrient digestibility, and elicited an increase in serum alpha-linolenic acid concentrations in healthy cats. Overall, these results clearly demonstrate that ground flaxseed can be used to modulate serum fatty acid concentrations and serve as a bioavailable source of alpha-linolenic acid in commercial cat food. Abstract We evaluated effects of dietary ground flaxseed on fecal and serum alpha-linolenic acid (ALA) concentrations, nutrient digestibility, and stool quality in female and male adult cats (n = 20 (8 males, 12 females); 3.95 ± 1.49 years of age (mean ± SD); 3.88 ± 0.82 kg BW). We hypothesized that adding ground flaxseed would increase serum ALA compared with feeding no flax, without changing nutrient digestibility. Cats were fed as-is 2.6% added-flaxseed (flax, n = 10) or no-flax (control, n = 10) diets (2.66 vs. 0.78% ALA of total fatty acids; crude protein 35%, fat 20%, fiber 3% as-fed) twice daily to maintain body weight for 28 days. Fecal collections were conducted on days 23–27 for total-tract nutrient digestibility, stool quality (scale 1–5; 1 = watery diarrhea, 5 = hard, dry, crumbly) and long-chain fatty acid (LCFA) analyses. Blood was collected on days 0, 14, and 28 for serum LCFA and chemistry analysis. Digestibility and fecal data were analyzed by ANOVA (SAS v9.4, Cary, NC, USA) and a repeated measures ANOVA for serum ALA. Flax-fed cats, compared with control-fed, had greater (p < 0.05) serum ALA after 14 days (4.00 vs. 0.71 µg/mL) and 28 days (7.83 and 3.67 µg/mL). No differences were observed in stool quality, and dry matter, protein, fat, and ALA digestibility. However, metabolizable energy was greater in the flax vs. control diet (4.18 vs. 3.91 kcal/g; p < 0.05). Overall, these data demonstrate that ground flaxseed added to cat diets increases serum ALA within 14 days, with no detriments to nutrient digestibility. We conclude that flaxseed can be used as a bioavailable source of ALA in cat diets.
The mixture of trees Factorized Distribution Algorithm

This paper introduces a Factorized Distribution Algorithm based on a mixture of trees distribution. The probabilistic model and the learning algorithm used differs to previous uses of probabilistic modeling in the context of Evolutionary Computation. Preliminary results show the algorithm is competitive, and some times superior to other Factorized Distribution Algorithms. We also illustrate how particular features of the search space can be employed during the search by conveniently selecting the mixture of trees parameters.
Exploring the Effect of Individual and Group Level Factors on the Level of Rural Residents’ Domestic Waste Sorting: Evidence from Shaanxi, China

Rural residents are the main agents of rural domestic waste-sorting; their level of sorting directly relates to the improvement of their rural living environment and the construction of “beautiful countryside”. Considering the data of 943 rural residents in Shaanxi Province, China, this study incorporates the factors at the individual and group levels and explores how personal norms and mianzi, which is the individual’s reputation and social status, at the individual level and social capital at the group level impact the level of rural residents’ domestic waste-sorting through an Ordered Probit model. The results show that personal norms and mianzi at the individual level play an important role in improving the level of rural residents’ domestic waste-sorting. Meanwhile, social capital (i.e., social networking, social trust, social participation, and social norms) at the group level has significant positive impacts on the level of rural residents’ domestic waste-sorting. Furthermore, mianzi plays a moderating role between personal norms, social capital, and the level of rural residents’ domestic waste-sorting, respectively. These findings are useful for the Chinese government to formulate a policy about enhancing the level of rural residents’ domestic waste-sorting to ease the rural environmental problem.
Generalized runge-kutta methods for dynamical systems

A numerical method is proposed for dynamical systems. We utilize the fact that special matrix exponentials can be exactly evaluated by the intrinsic library functions. Numerical examples are given, which show that the relative error s of the proposed method converge to a small constant and that the method faithfully approximates the dynamics of the nonlinear differential equations.
Genetic Variants of CITED2 Gene Promoter in Human Atrial Septal Defects: Case-Control Study and Cellular Functional Verification

Atrial septal defect (ASD) is one of the most common forms of congenital heart disease (CHD). Genetic variants in the coding region of the CITED2 gene are known to be significantly correlated with CHD, but the role of variants in the promoter region of CITED2 is unknown. We investigated variants in the promoter of the CITED2 gene in 625 subjects (332 ASD and 293 healthy controls) through Sanger sequencing. Four variants in the CITED2 gene promoter were found only in eight ASD patients with zero occurrence in the control subjects (one case of g.4078A>C(rs1165649373), one case of g.4240C>A(rs1235857801), four cases of g.4935C>T(rs111470468), two cases of g.5027C>T(rs112831934)). Cellular functional analysis showed that these four variants significantly changed the transcriptional activity of the CITED2 gene promoter in HEK-293 and HL-1 cells. Electrophoretic mobility change assay results and JASPAR database analysis demonstrated that these variants created or destroyed a series of possible transcription factor binding sites, resulting in changes in the expression of CITED2 protein. We conclude that the variants of CITED2 promoter in ASD patients affect the transcriptional activity and are likely involved in the occurrence and development of ASD. These findings provide new perspectives on the pathogenesis and potential therapeutic insights of ASD.
Targeting Capabilities of Native and Bioengineered Extracellular Vesicles for Drug Delivery

Extracellular vesicles (EVs) are highly promising as drug delivery vehicles due to their nanoscale size, stability and biocompatibility. EVs possess natural targeting abilities and are known to traverse long distances to reach their target cells. This long-range organotropism and the ability to penetrate hard-to-reach tissues, including the brain, have sparked interest in using EVs for the targeted delivery of pharmaceuticals. In addition, EVs can be readily harvested from an individual’s biofluids, making them especially suitable for personalized medicine applications. However, the targeting abilities of unmodified EVs have proven to be insufficient for clinical applications. Multiple attempts have been made to bioengineer EVs to fine-tune their on-target binding. Here, we summarize the current state of knowledge on the natural targeting abilities of native EVs. We also critically discuss the strategies to functionalize EV surfaces for superior long-distance targeting of specific tissues and cells. Finally, we review the challenges in achieving specific on-target binding of EV nanocarriers.
Cross-Cultural Adaptation of the Instrument “Nurse–Physician Relationship Survey: Impact of Disruptive Behavior in Patient Care” to the Spanish Context

Disruptive behavior in the healthcare context has an impact on patient care, healthcare personnel, and the health organization, and it also influences the therapeutic relationship, communication process, and adverse events. However, there is a lack of instruments that could be used for its analysis in the hospital care environment in the Spanish context. The objective of the study was to culturally adapt and perform a content validation of the tool “Nurse–Physician Relationship Survey: Impact of Disruptive Behavior on Patient Care”, to the Spanish content (Spain). An instrumental study was conducted, which included an analysis of conceptual and semantic equivalence. A panel of experts analyzed the translations, by analyzing the Content Validity Index (CVI) of the group of items in the scale through the Relevance Index (RI) and the Pertinence Index (PI). Only a single item obtained an RI value of 0.72, although with PI value of 0.81, with consensus reached for not deleting this item. The CVI of all the items was >0.80 for the mean value of the RI, as well as the PI. The instrument was adapted to the Spanish context and is adequate for evaluating the disruptive behaviors on nurse–physician relationships and its impact on patient care. However, the importance of continuing the analysis of the rest of the psychometric properties in future studies is underlined.
Estimation of rare event probabilities and extreme quantiles. Applications in the aerospace domain

Rare event dedicated techniques are of great interest for the aerospace industry because of the large amount money that can be lost because of risks associated with minute probabilities. This thesis is focused on the search of probability techniques able to estimate rare event probabilities and extreme quantiles associated with a black box system with static random inputs through two case studies from the industry. The first one is the estimation of the probability of collision between satellites Iridium and Cosmos. The cross-entropy (CE), the non-parametric adaptive importance sampling (NAIS) and an adaptive splitting technique (AST) are compared. Through the comparison, an improved version of NAIS is designed. Whereas NAIS needs to be initiated with a auxiliary random variable which straight away generates rare events, the adaptive NAIS (ANAIS) allows one to use the original input random as initial auxiliary density and therefore does not require a priori knowledge. The second case is the estimation of the safety zone with respect to the fall of a spacecraft booster. Though they can be estimated via ANAIS or AST, extreme quantiles are shown to be not adapted to spatial distribution. For that purpose, the minimum volume set (MVS) concept is chosen from the literature. The crude Monte Carlo (CMC) plug-in MVS estimator being not adapted to extreme level MVS estimation, both ANAIS and AST are adapted into plug-in extreme MVS estimators.These two algorithms outperform the CMC plug-in MVS estimator.
Mining Public Opinions on COVID-19 Vaccination: A Temporal Analysis to Support Combating Misinformation

This article presents a study that applied opinion analysis about COVID-19 immunization in Brazil. An initial set of 143,615 tweets was collected containing 49,477 pro- and 44,643 anti-vaccination and 49,495 neutral posts. Supervised classifiers (multinomial naïve Bayes, logistic regression, linear support vector machines, random forests, adaptative boosting, and multilayer perceptron) were tested, and multinomial naïve Bayes, which had the best trade-off between overfitting and correctness, was selected to classify a second set containing 221,884 unclassified tweets. A timeline with the classified tweets was constructed, helping to identify dates with peaks in each polarity and search for events that may have caused the peaks, providing methodological assistance in combating sources of misinformation linked to the spread of anti-vaccination opinion.
Snow-influenced floods are more strongly connected in space than purely rainfall-driven floods

Widespread floods that affect several catchments are associated with large damages and costs. To improve flood protection, a better understanding of the driving processes of such events is needed. Here, we assess how spatial flood connectedness varies with the flood generation process using a flood event classification scheme that distinguishes between rainfall-driven and snowmelt-influenced flood types. Our results show that the dominant flood generation processes in Europe vary by region, season, and event severity. Specifically, we show that severe floods are more often associated with snow-related processes than moderate events. In addition, we find that snow-influenced events show stronger spatial connections than rainfall-driven events. The spatial connectedness of rainfall-driven events depends on the rainfall duration, and the connectedness decreases with increasing duration. These findings have potential implications for flood risk in a warming climate, both locally and regionally. The projected decrease in the frequency of occurrence of snowmelt-influenced floods may translate into a decrease in the frequency of severe and widespread floods in catchments where snowmelt processes are important for flood generation.
Nonclassical properties of a deformed atom-cavity field state

We analyse here a nonclassical state produced by an atom-cavity field interaction. The two-level atom is passed through the single-mode electromagnetic cavity field. By deforming the field operators and introducing nonlinearity to the classic Jaynes–Cummings model, we explore the system in respect of a nonlinear Hamiltonian. Assuming that the atom is in an excited state and the field is in a coherent state initially, the analytic expression for the state vector of the entire system state vector is obtained. With the help of the derived state vector, we calculate the photon number distribution, Mandel's parameter, Wigner function, anti-bunching, squeezing properties and Q function etc.
"No One Knows Who I Am": What School Leaders Can Learn From ESL Teachers' Voices to Provide Equitable Education for Emergent Bilinguals

Studies have indicated that English as a Second Language (ESL) teachers face many challenges in meeting the needs of emergent bilinguals (EBs). Yet, little scholarship has addressed what actions school leaders can take to resolve teachers’ concerns. Through the voices of five ESL teachers from a district with a high number of EBs, this case study moves beyond listing the challenges ESL teachers face to discussing actions school leaders can take to address the needs of ESL teachers. More specifically, the participants describe a lack of leadership in promoting collaborations between teachers, ineffective implementation of a push-in model, and issues of time and assessment policy. Suggestions of actions include collaborative leadership with ESL teachers, distributing teaching of EBs a core responsibility for all teachers, valuing multiculturalism and multilingualism, and thinking beyond standardized testing.
The Role of Gender-Related Immune Genes in Childhood Acute Myeloid Leukemia

The study of immune genes and immune cells is highly focused in recent years. To find immunological genes with prognostic value, the current study examines childhood acute myeloid leukemia according to gender. The TARGET database was used to gather the “mRNA expression profile data” and relevant clinical data of children with AML. To normalize processing and find differentially expressed genes (DEG) between male and female subgroups, the limma software package is utilized. We identified prognostic-related genes and built models using LASSO, multivariate Cox, and univariate Cox analysis. The prognostic significance of prognostic genes was then examined through the processing of survival analysis and risk score (RS) calculation. We investigated the connections between immune cells and prognostic genes as well as the connections between prognostic genes and medications. Finally, five immune genes from the TARGET database have been identified. These immune genes are considerably correlated to the prognosis of male patients.
International human capital in the local labour market: experiences of the foreign-educated Kazakhstani graduates

ABSTRACT Using mixed methods research approach, this study explores the employment experiences of the Kazakhstani graduates with international human capital in the domestic labour market. Human and social capital theories and Spence’s signalling theory are utilised to explain and consider how investment into and internationalisation of those capitals and signalling attributes contribute to the graduates’ after-return labour market participation scenarios. The findings indicate that international education significantly improves graduate employability and widens opportunities. However, the limited options and capacity of the local labour market as well as the attitudinal differences between the Soviet era senior administration and foreign-educated graduates represent serious challenges.
Distributed event-triggered consensus in multi-agent systems with non-linear protocols

In this study, the distributed event-triggered consensus problem in multi-agent systems with non-linear protocols is discussed. In the proposed strategies, each agent adopts a local control based on a combination of non-linear functions of relative states, and the couplings among agents are not necessarily symmetric and constant. By using a graph-theoretical-reasoning based Lyapunov function, the authors present two kinds of distributed event-triggered strategies, namely state-dependent and time-dependent strategies. Through the transmission of states at discrete instants, the former can simultaneously reduce the updates of both control and communication. By virtue of global information such as the path between arbitrary two agents, the latter can decide the updating time sequence for each agent by its own state and a given time-dependent function. In both cases, a positive lower bound for inter-event times can be found such that the Zeno behaviour is eliminated. Numerical simulations show the effectiveness of the above two strategies.
Zeta-functions and transfer-operators for piecewise linear transformations.

Introduction. A transformation T on the interval [0, 1] is called piecewise monotonic if [0, 1] can be decomposed into a finite union of disjoint intervals Jt and T\Ji is continuous and monotone. One of the important methods for the description of the asymptotic behaviour of such transformations is the investigation of the transferoperators P associated with T (also called Perron-Frobenius-operator or Ruelle-Arakioperator). If /: [0, 1]—>C is measurable one defines Pf(x) = Σ g(y)f(y) where yeTi jc g: [0, 1] — * IR* is some given weight function.