Miracle-dz/UniFAR-FTUs huggingface dataset:
Insights into solute e ﬀ ects on elastic moduli in bcc Fe based solid solutions from ﬁrst-principles

Understanding the underlying mechanisms on how solutes modify elastic moduli of metals is essential in numerous areas spanning solid-state physics to materials selection in mechanical design. We perform ﬁrst-principles calculations to study the elastic moduli changes relative to (cid:11) -Fe for bcc Fe-based solid solutions, as solute content increases from 0 : 4 at. % to 1 : 85 at. %. Besides the “common ex-pectation” that the elastic moduli vary linearly with solute content in these homogeneous solid solutions, nonlinear variations are also observed in Fe-Mn system, which is attributed to the change in electronic environment of Fe solvent rather than in magnetic moment of solute Mn. At the elastic moduli linear regime, solutes modify the bulk modulus B and the polycrystalline shear modulus G through variations in the valence electron density n WS at boundary of Wigner-Seitz cells and the bonding strength, respectively. Interestingly, it is found that with increasing solute content, the change rate of n 2WS V m ( V m : mole volume) increases exponentially with the change rate of B , while the change rate of Debye temperature
A novel hybrid algorithm based on Harris Hawks for tumor feature gene selection

Background Gene expression data are often used to classify cancer genes. In such high-dimensional datasets, however, only a few feature genes are closely related to tumors. Therefore, it is important to accurately select a subset of feature genes with high contributions to cancer classification. Methods In this article, a new three-stage hybrid gene selection method is proposed that combines a variance filter, extremely randomized tree and Harris Hawks (VEH). In the first stage, we evaluated each gene in the dataset through the variance filter and selected the feature genes that meet the variance threshold. In the second stage, we use extremely randomized tree to further eliminate irrelevant genes. Finally, we used the Harris Hawks algorithm to select the gene subset from the previous two stages to obtain the optimal feature gene subset. Results We evaluated the proposed method using three different classifiers on eight published microarray gene expression datasets. The results showed a 100% classification accuracy for VEH in gastric cancer, acute lymphoblastic leukemia and ovarian cancer, and an average classification accuracy of 95.33% across a variety of other cancers. Compared with other advanced feature selection algorithms, VEH has obvious advantages when measured by many evaluation criteria.
Quantification of Uncertainity in Fire-Weather Forecasts: Some Results of Operational and Experimental Forecasting Programs

Abstract Fire-weather forecasts (FWFs) prepared by National Weather Service (NWS) forecasters on an operational basis are traditionally expressed in categorical terms. However, to make rational and optimal use of such forecasts, fire managers need quantitative information concerning the uncertainty inherent in the forecasts. This paper reports the results of two studies related to the quantification of uncertainty in operational and experimental FWFs. Evaluation of samples of operational categorical FWFs reveals that these forecasts contain considerable uncertainty. The forecasts also exhibit modest but consistent biases which suggest that the forecasters are influenced by the impacts of the relevant events on fire behavior. These results underscore the need for probabilistic FWFs. The results of a probabilistic fire-weather forecasting experiment indicate that NWS forecasters are able to make quite reliable and reasonably precise credible interval temperature forecasts. However, the experimental relative.
First insight into how stress exposure triggers Vibrio harveyi recipient successful conjugation

Conjugation is the most common horizontal gene transfer (HGT) process that can be affected by environmental change and promote bacterial virulence and drug resistance. However, it is unknown whether environmental changes can influence the conjugation ability of the marine fish pathogen Vibrio harveyi, thereby affecting its pathogenicity and drug resistance. This study systematically analyzes the effect of environmental stress on the ability of V. harveyi to obtain shuttle plasmids from Escherichia coli during conjugation. The results indicate that V. harveyi cannot receive shuttle plasmid pMMB207 without exposure to stress. However, certain stress exposure (37–46°C, 4%–16% ethanol, 0.14–0.56 mM SDS, 0.04~0.05 M NaOH, and 0.012–0.024 M HCl for 5–60 minutes) in the log phase of V. harveyi before conjugation successfully induces the fertility of the V. harveyi recipient in intergeneric mating with E. coli. In particular, ethanol and heat stress showed strong induction with up to 2.5 × 105 and 5.3 × 103 transconjugants when exposed to 16% ethanol for 10 minutes and 40°C for 60 minutes, respectively. Additionally, appropriate levels of NaOH (0.05 M, 10 minutes), SDS (0.42 mM, 5 minutes), and HCl (0.024 M, 5 minutes) lead to 2.3 × 103, 4.5 × 102, and 1.8 × 102 transconjugants, respectively. These results will help establish homologous recombination gene knockout technology and greatly advance molecular theoretical research on V. harveyi. They will also support the establishment of disease prevention and control strategies based on the interruption of the HGT process by environmental regulation.
A PDE approach to risk measures of derivatives

This paper proposes a partial differential equation (PDE) approach to calculate coherent risk measures for portfolios of derivatives under the Black-Scholes economy. It enables us to define the risk measures in a dynamic way and to deal with American options in a relatively effective way. Our risk measure is based on the representation form of coherent risk measures. Through the use of some earlier results the PDE satisfied by the risk measures are derived. The PDE resembles the standard Black-Scholes type PDE which can be solved using standard techniques from the mathematical finance literature. Indeed, these results reveal that the PDE approach can provide practitioners with a more applicable and flexible way to implement coherent risk measures for derivatives in the context of the Black-Scholes model.
Campaign of sky brightness and extinction measurements using a portable CCD camera

In this paper, we present the results of a 12-yr campaign devoted to monitoring the sky brightness affected by different levels of light pollution. Different sites characterized by different altitudes and atmospheric transparency have been considered. The standard photometric Johnson B and V bands were used. An extinction measurement was performed for each site and each night, along with a calibration of the instrument. These measurements have allowed us to build sky brightness maps of the hemisphere above each observing site; each map contains up to 200 data points spread around the sky. We have found a stop in zenith sky brightness growth at the two sites where a time series exists. Using zenith sky brightness measurements taken with and without extensive snow coverage, we weighted the importance of direct versus indirect flux in producing sky glow at several sites.
The Time Course of Cardiorespiratory Adaptations to Rowing Indoor Training in Post-Menopausal Women

Background: Post-menopausal women have impaired cardiorespiratory responses to exercise compared to young women. Exercise training may counterbalance impairments, but the time-dependent effects of exercise training remain unclear. The current study aims to investigate the effects of rowing training on maximal aerobic capacity and time-course cardiorespiratory adaptations in older women. Methods: Female participants (n = 23) were randomly allocated to the experimental group (EXP; n = 23; 66 ± 5 years old) enrolled in rowing exercise training and control group (CON; n = 10; 64 ± 4 years old). The cardiopulmonary exercise test (CET) was performed in a cycle ergometer pre- and post-interventions. Oxygen uptake (VO2), stroke volume (SV), cardiac output (CO), and HR were recorded during CET and analyzed at the peak of the exercise. HR was monitored during exercise recovery, and the index of HRR was calculated by ΔHRR (HRpeak—HR one-minute recovery). Every two weeks, Rowing Stepwise Exercise (RSE) in a rowing machine was performed to track specific adaptations to the exercise modality. HR was continuously recorded during RSE and corrected for the average power of each step (HR/watts). The rowing training protocol consisted of three weekly sessions of 30 min at an intensity corresponding to 60–80% of peak HR for ten weeks. Results: Rowing exercise training increased VO2, SV, and CO at the peak of the CET, and ΔHRR. Increased workload (W) and reduced HR response to a greater achieved workload (HR/W) during RSE were observed after six weeks of training. Conclusions: Rowing exercise training is a feasible method to improve cardiorespiratory performance, vagal reactivation and heart rate adjustments to exercise in older women.
The analysis of variance in experimental psychology: 1934–1945

The paper provides a survey of early applications of analysis of variance in psychology, concentrating on experimental psychology, but with one or two brief excursions into educational psychology. The work demonstrates that incorporating the technique into psychology was a long and painful process. This was due more to the substantive implications of the method than to the purely practical matters of increased arithmetical labour and novelty of language that the new technique brought with it. Such a view differs radically from that expressed by commentators working during the period covered by the paper and later. Finally, a brief account of how experiments were conducted and analysed prior to analysis of variance is provided so as to point up the sources of difficulty with the method. A special section is devoted to early attempts to cope with the concept of interaction.
Quantitative Diagnosis Progress of Ultrasound Imaging Technology in Thyroid Diffuse Diseases

High-frequency ultrasound (HFUS), the imaging modality of choice for thyroid screening, is most commonly used in the study of diffuse thyroid disease (DTD) with Hashimoto’s thyroiditis (HT) and Graves’ disease (GD). DTD can involve thyroid function and severely affect life quality, so early diagnosis is important for the development of timely clinical intervention strategies. Previously, the diagnosis of DTD relied on qualitative ultrasound imaging and related laboratory tests. In recent years, with the development of multimodal imaging and intelligent medicine, ultrasound and other diagnostic imaging techniques have gradually become more widely used for quantitative assessment of the structure and function of DTD. In this paper, we review the current status and progress of quantitative diagnostic ultrasound imaging techniques for DTD.
Fuzzy constraint satisfaction

In this paper the issue of soft constraint satisfaction is discussed from a fuzzy set theoretical point of view. A fuzzy constraint is considered as a fuzzy relation. Different possible definitions for the degree of joint satisfaction of a set of fuzzy constraints are given, covering other specific soft constraint satisfaction problem (CSP) types such as partial and hierarchical CSP. It is shown that the classical CSP solving heuristics based on variable and value evaluations can be generalised and used to guide the solution construction process for solving fuzzy CSPs, and that the heuristic search can be replaced by branch-and-bound search. The solution process is illustrated with an example from the CSP literature. Finally, research issues are discussed. <<ETX>>
Graph Based and Multifractal Analysis of Financial Time Series Model by Continuum Percolation

Abstract Applying multifractal centered moving average and two graph based analysis, we investigate and compare statistical behaviors of return time series of some Chinese market data and a financial model developed by the continuum percolation system. The local interaction or influence among traders in the actual market is constructed by the continuum percolation, and a cluster of continuum percolation is applied to define the cluster of traders sharing the same opinion about the market. The empirical research shows that the simulation data of the model exhibits fractal and multifractal features. Further, we find that the degree distribution of visibility graph for the simulation series has power-law tails, and the corresponding mean path length growth shows the “small-world” effect. All these features are in agreement with real market data.
On the Convergence of Finite Element Method for Second Order Elliptic Interface Problems

The purpose of this paper is to study the convergence of finite element approximation to the exact solution of general self-adjoint elliptic equations with discontinuous coefficients. Due to low global regularity of the solution, it is difficult to achieve optimal order of convergence with classical finite element methods [Numer. Math. 1998; 79:175–202]. In this paper, an isoparametric type of discretization is used to prove optimal order error estimates in L 2 and H 1 norms when the global regularity of the solution is low. The interface is assumed to be of arbitrary shape and is smooth for our purpose. Further, for the purpose of numerical computations, we discuss the effect of numerical quadrature on finite element solution, and the related optimal order estimates are also established.
THE FINITE-SAMPLE PROPERTIES OF MAXIMUM LIKELIHOOD ESTIMATORS IN MULTINOMIAL PROBIT MODELS

In this paper we discuss the finite-sample properties of maximum likelihood estimators of multinomial probit model. Sample sizes ranging from 20 to 200 at interval of 10 are tested. For each sample size, we estimated 9 utility specifications under different error covariance matrix assumptions. Robust variance matrix is used to get the asymptotic covariance of estimators for each model. We use Monte Carlo experiments to generate the data sets and replicate 500 times for each experiment. We found that when the size of standardized parameter of generic variable is greater than 0.5 and the sample size is greater than 60, the odds of getting significant estimator that is close to the true value are larger than 0.9. When the size of standardized parameter is small, e.g., less than 0.25, a sample size of at least 170 is needed to get good results.
Circadian Clock Contributes to Modulate Salinity Stress-Responsive Antioxidative Mechanisms and Chloroplast Proteome in Spinacia oleracea

Extreme abiotic stresses such as drought, salinity, and temperature reduce crop productivity significantly and pose a serious threat to the area of land used for agriculture. Therefore, there is a pressing need to create crops that can thrive in these circumstances. It has been noted that plants can maintain defense mechanisms during any environmental changes and anticipate diurnal patterns correct to a circadian-based clock. Therefore, the main aim of this study was to investigate the role of circadian core oscillators in response to salinity stress in an important vegetable crop, spinach, and obtain evidence to better understand salinity stress adaptation for crop productivity. Therefore, the current study was carried out to examine the circadian clock-based (morning–evening loop) salinity stress defense mechanism in spinach (Spinacia oleracea), a leafy vegetable crop with significant economic importance and health benefits. In the presence of dawn and dusk, the circadian clock-based defense mechanism was observed using the genotypes “Delhi Green” and “Malav Jyoti. ” A photoperiodic rhythm consists of 4-h intervals for 12 h (morning–evening loop) in spinach was demonstrated under the salinity stress treatments (20 mM and 50 mM). The clock-controlled a large fraction of growth parameters such as plant height, biomass, and root-shoot ratio under salinity stress. Conversely, salinity stress resulted in upregulation of antioxidative parameters such as superoxide dismutase, ascorbate peroxidase, catalase, and other stress markers such as thiobarbituric acid reactive substances, proline content, and localizations of H2O2 and O2−1 but was altered and maintained at a certain photoperiodic time interval of the circadian clock. In distinction to results observed from antioxidative measurements performed with an early and late circadian duration of salt-treated plants, 10 am and 2 pm were revealed to be the rhythmic times for controlling salinity stress. Likewise, comprehensive measurements of the photosynthetic system under salinity stress at specific photoperiodic circadian time intervals, including net-photosynthetic rate, transpiration, stomatal conductance, PSII quantum yield, and stomata structure, were made at 10 am and 2 pm. The salinity stress response was down-streamed and the clock also regulated chloroplastic protein expression. Thus, according to our findings, photoperiodic circadian rhythms, particularly the morning–evening loop, enhanced plant survival rates by modulating cellular antioxidant mechanisms and chloroplastic proteins that further helped to reduce the effects of salinity stress.
Je spev jariabka hôrneho (Tetrastes bonasia) doménou samcov?

: In most birds, males are responsible for territory defence and mate attraction using a song. Females’ song is less frequent and usually produced for other reasons. The female song has also been reported in Hazel Grouse (Tetrastes bonasia ), but has not received sufficient attention. In the northern part of the Horná Orava Protected Landscape Area, we recorded songs of ten females and nine males from 2014 to 2020. Individuals were provoked by imitating a species-specific song with a lure. This work presents the basic acoustic traits of Hazel Grouse song and sex-based song differences. In addition, we point out the different functions of the male and female songs. Specifically, males sang longer songs at higher frequencies than females. Moreover, in spring, males actively responded to the imitation of the female song, suggesting that the females attract males by singing. In the spring and autumn, males reacted to the imitation of songs of both sexes, indicating that the male songs serve to defend the territory. Females responded exclusively to the imitation of female songs, thus indicating that they were
Theory of dynamic critical phenomena

An introductory review of the central ideas in the modern theory of dynamic critical phenomena is followed by a more detailed account of recent developments in the field. The concepts of the conventional theory, mode-coupling, scaling, universality, and the renormalization group are introduced and are illustrated in the context of a simple example\char22{}the phase separation of a symmetric binary fluid. The renormalization group is then developed in some detail, and applied to a variety of systems. The main dynamic universality classes are identified and characterized. It is found that the mode-coupling and renormalization group theories successfully explain available experimental data at the critical point of pure fluids, and binary mixtures, and at many magnetic phase transitions, but that a number of discrepancies exist with data at the superfluid transition of $^{4}\mathrm{He}$.
On Perturbation Measure of Sets - Properties

: In this paper we describe a new measure of remoteness between sets described by nominal values. The introduced measures of perturbation of one set by another are considered instead of commonly used distance between two sets. The operations of the set theory are op-erated and the considered measures describe changes of the perturbed second set by adding the first one or vice versa. The values of the measure of sets’ perturbation are range between 0 and 1, and in general, are not symmetric – it means that the perturbation of one set by another is not the same as the perturbation of the second set by the first one.
Idealized model for stratocumulus cloud layer thickness

Equilibrium solutions are constructed using an idealized model for mixed and partially mixed boundary layers to show the dependence of the equilibrium cloud layer thickness on different physical processes. The condition when a mixed layer becomes cloud-free is reduced to a comparison between three pressure scales, associated with the surface wind and divergence, the radiative cooling and the subsaturation of the entrained air. The evaporation of layer cloud by cloud-top mixing is also formulated in terms of simple pressure scales.
Research on Precipitation Prediction Model Based on Extreme Learning Machine Ensemble

Precipitation is a significant index to measure the degree of drought and flood in a region, which directly reflects the local natural changes and ecological environment. It is very important to grasp the change characteristics and law of precipitation accurately for effectively reducing disaster loss and maintaining the stable development of a social economy. In order to accurately predict precipitation, a new precipitation prediction model based on extreme learning machine ensemble (ELME) is proposed. The integrated model is based on the extreme learning machine (ELM) with different kernel functions and supporting parameters, and the submodel with the minimum root mean square error (RMSE) is found to fit the test data. Due to the complex mechanism and factors affecting precipitation change, the data have strong uncertainty and significant nonlinear variation characteristics. The mean generating function (MGF) is used to generate the continuation factor matrix, and the principal component analysis technique is employed to reduce the dimension of the continuation matrix, and the effective data features are extracted. Finally, the ELME prediction model is established by using the precipitation data of Liuzhou city from 1951 to 2021 in June, July and August, and a comparative experiment is carried out by using ELM, long-term and short-term memory neural network (LSTM) and back propagation neural network based on genetic algorithm (GA-BP). The experimental results show that the prediction accuracy of the proposed method is significantly higher than that of other models, and it has high stability and reliability, which provides a reliable method for precipitation prediction.
Foundry manufacturing of tight-confinement, dispersion-engineered, ultralow-loss silicon nitride photonic integrated circuit

The foundry development of integrated photonics has revolutionized today's optical interconnect and datacenters. Over the last decade, we have witnessed the rising of silicon nitride (Si$_3$N$_4$) integrated photonics, which is currently transferring from laboratory research to foundry manufacturing. The development and transition are triggered by the ultimate need of low optical loss offered by Si$_3$N$_4$, which is beyond the reach of silicon and III-V semiconductors. Combined with modest Kerr nonlinearity, tight optical confinement and dispersion engineering, Si$_3$N$_4$ has today become the leading platform for linear and Kerr nonlinear photonics, and has enabled chip-scale lasers featuring ultralow noise on par with table-top fiber lasers. However, so far all the reported fabrication processes of tight-confinement, dispersion-engineered Si$_3$N$_4$ photonic integrated circuit (PIC) with optical loss down to few dB/m have only been developed on 4-inch or smaller wafers. Yet, to transfer these processes to established CMOS foundries that typically operate 6-inch or even larger wafers, challenges remain. In this work, we demonstrate the first foundry-standard fabrication process of Si$_3$N$_4$ PIC with only 2.6 dB/m loss, thickness above 800 nm, and near 100% fabrication yield on 6-inch wafers. Such thick and ultralow-loss Si$_3$N$_4$ PIC enables low-threshold generation of soliton frequency combs. Merging with advanced heterogeneous integration, active ultralow-loss Si$_3$N$_4$ integrated photonics could pave an avenue to addressing future demands in our increasingly information-driven society.