Miracle-dz/UniFAR-FTUs huggingface dataset:
Correlation Between Financial Performance Indicators and Capital Structure of Coal Mining Industry Listed on the Indonesia Stock Exchange

This research examines the correlation between capital structure (as proxied by Debt-to-Equity Ratio) and several financial performance indicators, including profitability, asset structure, liquidity, and firm size. This research focuses on 18 coal mining companies listed on the Indonesia Stock Exchange (IDX) by at least 2020. The data is derived from the financial reports published on the IDX between 2020 and 2022. Multiple Linear Regression technique is being employed to determine the correlations. Before employing the Multiple Linear Regression technique, several tests were conducted to examine the data's validity and reliability, including normality, multicollinearity, autocorrelation, and heteroscedasticity tests. Multiple Linear Regression is employed after the data passes the tests, consisting of partial regression, ANOVA, and goodness-of-fit tests. This research found that profitability and liquidity negatively correlate with capital structure. At the same time, asset structure and firm size positively correlate with capital structure. Overall, the result of this research supports Pecking Order Theory, in which firms are preferred to use internal financing first. When firms generate higher profits and cash flow, they may consider re-balancing external financing. This research also concludes that profitability, asset structure, liquidity, and firm size represent 47.7% of the variables correlated with capital structure. Future research may be conducted to seek other variables that have not been included in this research yet but are correlated with capital structure.
Promising Novel Biomarkers for Hepatocellular Carcinoma: Diagnostic and Prognostic Insights

Abstract The systemic therapy landscape for hepatocellular carcinoma is rapidly evolving, as the recent approvals of checkpoint inhibitor-based regimens such as atezolizumab–bevacizumab and durvalumab–tremelimumab in advanced disease have led to an expanding therapeutic armamentarium. The development of biomarkers, however, has not kept up with the approvals of new agents. Nevertheless, biomarker research for hepatocellular carcinoma has recently been growing at a rapid pace. The most active areas of research are biomarkers for early detection and screening, accurate prognostication, and detection of minimal residual disease following curative intent therapies, and, perhaps most importantly, predictive markers to guide selection and sequencing of the individual agents, including tyrosine kinase inhibitors and immunotherapy. In this review, we briefly summarize the recent developments in systemic therapeutics for hepatocellular carcinoma, introduce the key completed and ongoing prospective and retrospective studies evaluating diagnostic, prognostic, and predictive biomarkers with high clinical relevance, highlight several potentially important areas of future research, and share our insights for each biomarker.
Identification of the Light-Harvesting Chlorophyll a/b Binding Protein Gene Family in Peach (Prunus persica L.) and Their Expression under Drought Stress

In higher plants, light-harvesting chlorophyll a/b binding (Lhc) proteins play a vital role in photosynthetic processes and are widely involved in the regulation of plant growth, development, and response to abiotic stress. However, the Lhc gene family has not been well identified in peaches (Prunus persica L.). In this study, 19 PpLhc genes were identified in the peach genome database, which were unevenly distributed on all chromosomes. Phylogenetic analysis demonstrated that PpLhc proteins could be divided into three major subfamilies, each of whose members had different exon–intron structures but shared similar conserved motifs. A total of 17 different kinds of cis-regulatory elements were identified in the promoter regions of all PpLhc genes, which could be classified into three categories: plant growth and development, stress response, and phytohormone response. In addition, transcriptomic data analysis and RT-qPCR results revealed that the expression profiles of some PpLhc genes changed under drought treatment, suggesting the crucial roles of Lhc genes in the regulation of plant tolerance to drought stress. Taken together, these findings will provide valuable information for future functional studies of PpLhc genes, especially in response to drought stress.
Identification of Physical Parameters of a Porous Material Located in a Duct by Inverse Methods

Lined ducts with porous materials are found in many industrial applications. To understand and simulate the acoustic behaviour of these kinds of materials, their intrinsic physical parameters must be identiﬁed. Recent studies have shown the reliability of the inverse approach for the determination of these parameters. Therefore, in the present paper, two inverse techniques are proposed: the ﬁrst is the multilevel identiﬁcation method based on the simplex optimisation algorithm and the second one is based on the genetic algorithm. These methods are used of the physical parameters of a simulated case of a porous material located in a duct by the computation of its acoustic transfer, scattering, and power attenuation. The results obtained by these methods are compared and discussed to choose the more eﬃcient one.
Quantum fields as Cosmic Censors in (2 + 1)-dimensions

We discuss the effect of quantum fields on classical background spacetimes which contain timelike singularities. We do so for the case that the background is a [Formula: see text]-dimensional BTZ spacetime, whether corresponding to a rotating black hole ([Formula: see text]) or to a naked conical singularity ([Formula: see text]). In the black hole case, scalar quantum fields render its Cauchy horizon unstable, while for the conical geometry, they produce a horizon around the naked singularity. Thus, quantum effects improve the predictability of the spacetime acting as effective Cosmic Censors.
MARS: selecting basis and knots with the empirical Bayes method.

The multivariate adaptive regression spline (MARS), proposed by Friedman (1991), estimates regression structure including interaction terms adaptively with truncated power spline basis functions. However, it adopts the generalized cross-validation criterion to add and prune basis functions, and hence it tends to choose such large numbers of basis functions that estimated regression structure may not be easily interpreted. On the other hand, some Bayesian approaches incorporated in MARS have been proposed, in which the reversible jump MCMC algorithm is adopted. However, they generate enormous combinations of basis functions, from which it would be difficult to obtain clear interpretation on regression structure. An empirical Bayes method to select basis functions and knots in MARS is proposed, with taking both advantages of the frequentist model selection approach and the Bayesian approach. A penalized likelihood approach is used to estimate basis coefficients for given basis functions, and the Akaike Bayes information criterion (ABIC) is used to determine the number of basis functions. It is shown that the proposed method gives estimation of regression structure which is relatively simple and easy to interpret for some example data sets.
Search for two-frequency motion modes of single-mass vibratory machine with vibration exciter in the form of passive auto-balancer

Dynamics of a single-mass vibratory machine with rectilinear translational motion of the platform and a vibration exciter in the form of a ball, a roller, or a pendulum auto-balancer was analytically explored. The steady-state motion modes, close to dual-frequency modes were found. At these motions, loads in the auto-balancer create constant imbalance, cannot catch up with the rotor and get stuck at a certain frequency. In this way, loads operate as the first vibration exciter, exciting vibrations at frequency of the loads getting stuck. The second vibration exciter is formed by unbalanced mass on the auto-balancer body. The mass rotates at rotor speed and excites more rapid vibrations with this frequency. It was found that despite a strong asymmetry of supports, the auto-balancer excites almost perfect dual-frequency vibrations. Deviations from the dual-frequency law are proportional to the ratio of loads’ mass to the mass of the entire machine and do not exceed 2 %. It was established that at small forces of external and internal resistance, when the loads’ mass is much smaller than the platform’s mass, etc., there are three characteristic rotor speeds. These speeds are larger than the resonance velocity of platform oscillations. At the same time: – at the rotor speeds smaller than the first characteristic speed, there is only frequency when the loads get stuck, in this case it is smaller than the resonance velocity of platform oscillations; – at the above-resonance rotor speeds, located between the first and the second characteristic speeds, there are three frequencies when the loads get stuck, among which only one is below-resonance; – at the above-resonance rotor speeds, located between the second and the third characteristic speeds, there are three frequencies of the loads getting stuck, in this case, they are all above-resonance; – at the above-resonance rotor speeds, exceeding the third characteristic speed, there is only one frequency when the loads get stuck, in addition, it is above-resonant and close to the rotor speed. Only at the rotor speeds smaller than the second characteristic speed, there always exists one, and only one, below-resonance frequency of the loads getting stuck
CFD study of the bubble generation process in a T-junction with inversed flows

Two-phase flow applications are of great interest in the space sector thanks to its advantages, in the recent years, the research on this subject has increased considerably. Some examples can be found in space bioreactors, chemical contactors, life-support systems for human exploration and development of space, etc. Despite the great effort on understanding the behaviour of two-phase flows in microgravity, there are still many unknowns, therefore, further research is needed. In this study, we have dedicated our work to analyse the bubble generation of the water-air combination in a T-junction capillary. The simulations have been performed in a microgravity environment due to the very different behavior when compared to the one observed in the presence of gravitational forces, as well as, despite there is a lot of research in this field, there is still much more to be done. The open source program OpenFoam is used as the main tool for our simulations and Paraview as a post-processing tool. The InterFoam solver is selected to use in order to simulate laminar flow with two incompressible and isothermal phases. The study of numerical simulations has been carried out to compare it with experimental data and therefore, validate the software for this use. Before obtaining the results, convergence tests on the mesh have been performed, in addition to a study to detach the bubbles from the walls, focusing on the contact angle and wettability condition. We validated our mesh and selected the best boundary conditions to perform the finals tests. In the results, we carried out the simulations for three groups of combinations of velocities with U_SL=0.106 m/s, U_SL=0.318 m/s, and U_SL=0.531 m/s and different gas superficial velocity to analyse the behaviour of the bubble frequency, volume, velocity, and longitude. We obtained that simulations and experiments are really similarly qualitatively, with some differences quantitatively. Besides, they adequately reproduced the bubbles formation. By analysing all the parameters, we observe that for lower liquid superficial velocities the simulations approach perfectly to the experiments while increasing its velocity the simulations start having more fluctuations and move away from the experimental data.
Nonparametric Bayesian Methods for Extracting Structure from Data

One desirable property of machine learning algorithms is the ability to balance the number of parameters in a model in accordance with the amount of available data. Incorporating nonparametric Bayesian priors into models is one approach of automatically adjusting model capacity to the amount of available data: with small datasets, models are less complex (require storing fewer parameters in memory), whereas with larger datasets, models are implicitly more complex (require storing more parameters in memory). Thus, nonparametric Bayesian priors satisfy frequentist intuitions about model complexity within a fully Bayesian framework. This thesis presents several novel machine learning models and applications that use nonparametric Bayesian priors. We introduce two novel models that use flat, Dirichlet process priors. The first is an infinite mixture of experts model, which builds a fully generative, joint density model of the input and output space. The second is a Bayesian biclustering model, which simultaneously organizes a data matrix into block-constant biclusters. The model capable of efficiently processing very large, sparse matrices, enabling cluster analysis on incomplete data matrices. We introduce binary matrix factorization, a novel matrix factorization model that, in contrast to classic factorization methods, such as singular value decomposition, decomposes a matrix using latent binary matrices. We describe two nonparametric Bayesian priors over tree structures. The first is an infinitely exchangeable generalization of the nested Chinese restaurant process [11] that generates data-vectors at a single node in the tree. The second is a novel, finitely exchangeable prior generates trees by first partitioning data indices into groups and then by randomly assigning groups to a tree. We present two applications of the tree priors: the first automatically learns probabilistic stick-figure models of motion-capture data that recover plausible structure and are robust to missing marker data. The second learns hierarchical allocation models based on the latent Dirichlet allocation topic model for document corpora, where nodes in a topic-tree are latent “super-topics”, and nodes in a document-tree are latent categories. The thesis concludes with a summary of contributions, a discussion of the models and their limitations, and a brief outline of potential future research directions.
Acute stress imparts a transient benefit to task-switching that is not modulated following a single bout of exercise

Introduction Cognitive flexibility represents a core component of executive function that promotes the ability to efficiently alternate—or “switch”—between different tasks. Literature suggests that acute stress negatively impacts cognitive flexibility, whereas a single bout of aerobic exercise supports a postexercise improvement in cognitive flexibility. Here, we examined whether a single bout of aerobic exercise attenuates a stress-induced decrement in task-switching. Materials and Methods Forty participants (age range = 19–30) completed the Trier Social Stress Test (TSST) and were randomized into separate Exercise or Rest groups entailing 20-min sessions of heavy intensity exercise (80% of heart rate maximum via cycle ergometer) or rest, respectively. Stress induction was confirmed via state anxiety and heart rate. Task-switching was assessed prior to the TSST (i.e., pre-TSST), following the TSST (i.e., post-TSST), and following Exercise and Rest interventions (i.e., post-intervention) via pro- (i.e., saccade to veridical target location) and antisaccades (i.e., saccade mirror-symmetrical to target location) arranged in an AABB task-switching paradigm. The underlying principle of the AABB paradigm suggests that when prosaccades are preceded by antisaccades (i.e., task-switch trials), the reaction times are longer compared to their task-repeat counterparts (i.e., unidirectional prosaccade switch-cost). Results As expected, the pre-TSST assessment yielded a prosaccade switch cost. Notably, post-TSST physiological measures indicated a reliable stress response and at this assessment a null prosaccade switch-cost was observed. In turn, post-intervention assessments revealed a switch-cost independent of Exercise and Rest groups. Conclusion Accordingly, the immediate effects of acute stress supported improved task-switching in young adults; however, these benefits were not modulated by a single bout of aerobic exercise.
Clinical Analysis of the Colorectal Cohort within the Wales Cancer Biobank: A Study of Outcomes and Genetic Screening

Over the last 12 years, the Wales Cancer Biobank (WCB) has consented to more than 2000 patients with colorectal cancer (CRC). From these patients, clinical data has been collected and patients have been followed through their cancer journey. Clinical data from these patients have been analyzed to identify any correlation between disease grade and outcome. In a small cohort, consisting of 407 patients, WCB has performed genetic analysis on patient primary tumor samples, identifying and characterizing mutations in the KRAS, NRAS, BRAF, PIK3CA and TP53 genes. The majority of patients with CRC who were consented to WCB were male with a mean age of 69 years and received surgery as the primary treatment for their disease. Pathology and disease-free survival data confirmed worse prognoses associated with more advanced disease. Heterogeneity within the primary tumor was explored in a subgroup of patients. Analysis of the KRAS and TP53 genes confirmed that more than 40% of CRC patients who were tested, harbored a genetic mutation within these genes in their primary tumor. Due to the limited sample size tested, most mutations did not show significant differences in disease-free survival, however, mutation of the BRAF gene did show a decrease in the disease specific survival, in keeping with the published data. Analysis of the patients diagnosed with
Stratigraphy and palaeoenvironments in the upper Turonian to lower Coniacian of the Saxonian Cretaceous Basin (Germany)– insights from calcareous and agglutinated foraminifers

: Besen, R.M. , Achilles, M. , Alivernini, M. , Voigt, T. , Frenzel, P. and Struck, U. 2022. Stratigraphy and palaeo-environments in the upper Turonian to lower Coniacian of the Saxonian Cretaceous Basin (Germany) – insights from calcareous and agglutinated foraminifers. Acta Geologica Polonica , 72 (2), 159–186. Warszawa. Upper Turonian to lower Coniacian marls of the Strehlen Formation of the Graupa 60/1 core were investigated for their foraminiferal content to add stratigraphical and palaeoenvironmental information about the transitional facies zone of the Saxonian Cretaceous Basin. Further comparison with foraminiferal faunas of the Brausnitzbach Marl (Schrammstein Formation) were carried out to clarify its relationship to the marls of the Graupa 60/1 core. Tethyan agglutinated marker species for the late Turonian to early Coniacian confirm the proposed age of the marls of the Graupa 60/1 core and the Brausnitzbach Marl. The palaeoenvironment of the marls reflects middle to outer shelf conditions. The maximum flooding zones of genetic sequences TUR6, TUR7 and CON1 could be linked to acmes of foraminiferal species and foraminiferal morphogroups. In general, a rise of the relative sea-level can be recognised from the base to the top of the marls of the Graupa 60/1 core. While agglutinated foraminiferal assemblages suggest a generally high organic matter influx and variable but high productivity in the Graupa 60/1 core, the Brausnitzbach Marl deposition was characterized by moderate productivity and a generally shallower water depth.
Event-Triggered Robust Stabilization of Nonlinear Input-Constrained Systems Using Single Network Adaptive Critic Designs

In this paper, we study the event-triggered robust stabilization problem of nonlinear systems subject to mismatched perturbations and input constraints. First, with the introduction of an infinite-horizon cost function for the auxiliary system, we transform the robust stabilization problem into a constrained optimal control problem. Then, we prove that the solution of the event-triggered Hamilton–Jacobi–Bellman (ETHJB) equation, which arises in the constrained optimal control problem, guarantees original system states to be uniformly ultimately bounded (UUB). To solve the ETHJB equation, we present a single network adaptive critic design (SN-ACD). The critic network used in the SN-ACD is tuned through the gradient descent method. By using Lyapunov method, we demonstrate that all the signals in the closed-loop auxiliary system are UUB. Finally, we provide two examples, including the pendulum system, to validate the proposed event-triggered control strategy.
Efforts to Increase the Social Care of Middle School Students with Classical Guidance Service Tools

It is necessary to help students from all parties, especially supervising and supervising teachers. The goal is that students are aware of the growth and development of a sense of social welfare, especially in the school environment and its surroundings. The purpose of this research is to develop and test the acceptability and effectiveness of classic counseling tools to increase the social well-being of high school students. This research is a type of research that uses 4D development methods (Define, Design, Develop and Disseminate). This study involved 3 experts in the field of guidance and counseling and 2 people who tested the acceptance of classic counseling tools. In this study, data was collected using a questionnaire, which was analyzed using the Content Validity Ratio (CVR) formula. The results of the content validity index (CVI) and independent t.CVR analysis showed that all the goal statements in the questionnaire were accepted and received a CVI score of 1 category very good or exceptional, so the classical teaching device corresponds to acceptance criteria. The effectiveness of the Classical Tutoring Service device was tested on 30 Grade IX students of SMP Negeri 2 Singarajan using a Pretest-Posttest Control Group Design experimental design. The results of the t-test show a significant value of 0.00, which means that the use of classic counseling services tools is effective in increasing the social well-being of high school students.
On the Orographically Generated Low-Level Easterly Jet and Severe Downslope Storms of March 2006 over the Tacheng Basin of Northwest China

A high-latitude low-level easterly jet (LLEJ) and downslope winds, causing severe dust storms over the Tacheng basin of northwestern China in March 2006 when the dust source regions were previously covered by snow with frozen soil, are studied in order to understand the associated meteorological conditions and the impact of complex topography on the generation of the LLEJ. Observational analyses show the development of a large-scale, geostrophically balanced, easterly flow associated with a northeastern high pressure and a southeastern low pressure system, accompanied by a westward-moving cold front with an intense inversion layer near the altitudes of mountain ridges. A high-resolution model simulation shows the generation of an LLEJ of near-typhoon strength, which peaked at about 500 m above the ground, as well as downslope windstorms with marked wave breakings and subsidence warming in the leeside surface layer, as the large-scale cold easterly flow moves through a constricting saddle pass and across a higher mountain ridge followed by a lower parallel ridge, respectively. The two different airstreams are merged to form an intense LLEJ of cold air, driven mostly by zonal pressure gradient force, and then the LLEJ moves along a zonally oriented mountain range to the north. Results indicate the importance of the lower ridge in enhancing the downslope winds associated with the higher ridge and the importance of the saddle pass in generating the LLEJ. We conclude that the intense downslope winds account for melting snow, warming and drying soils, and raising dust into the air that is then transported by the LLEJ, generated mostly through the saddle pass, into the far west of the basin.