Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimation of soil carbon pools under major cropping systems of Mayiladuthurai district of Cauvery Delta Zone, Tamil Nadu, India

Soil organic carbon (SOC) is a potential indicator of soil quality and ecosystem sustainability. The present study aimed to evaluate SOC pools under major cropping systems of Mayiladuthurai district of Tamil Nadu. The composite samples were collected from two depths (0-15 and 15-30 cm) by stratified random sampling and were analysed for pH, EC (Electrical conductivity), C fractions, inorganic carbon and permanganate oxidisable carbon by standard procedures. The SOC content under different land use was in the order of Forestry > Rice – pulses > Rice – cotton > Sugarcane > Uncultivated. The mean SOC content of the study area was 12.58 Mg ha-1, where the majority of the area falls under low to medium rating of SOC. Hence, cultivation practices should incorporate activities that increase SOC to maintain soil quality. SOC was positively correlated with fractions of carbon – CVL (r = 0.37**), CL (r = 0.65**) and CLL (r = 0.58**), indicating changes in land use would affect the carbon dynamics of the ecosystem. The root biomass, aeration status, microbial activity, nutrient reserves and inherent soil characteristics influenced SOC to decrease with depth. The PCA analysis revealed that the variation in carbon dynamics of the study area was influenced by SOC, CLC, CLL and non-labile carbon due to differences in land management practices. Therefore, such soil management practices will be a powerful tool to sequester carbon, which supplements climate change mitigation.
Effects of a random cubic spring on the longitudinal dynamics of a bar excited by a Gaussian white noise

The study of the stochastic dynamics of continuous structures coupled with discrete elements is of interest in some fields of structural engineering. In this way, this papers deals with the analysis of the effects induced by a cubic spring, with gamma distributed random stiffness, on the longitudinal dynamics of an elastic bar which is also coupled with linear spring and a lumped mass. This system is subjected to a viscous dissipation mechanism and is excited by a Gaussian white noise. The model equations are discretized using the Galerkin method, and the propagation of uncertainties through the model are computed by the Monte Carlo method. Numerical simulations, indexed by the mean value of the cubic spring random stiffness, are conducted and show that this random cubic nonlinearity induces an increase in the level of uncertainty of the system response, in comparison with the linear case. Also, the random nonlinearity generates system responses which exhibit asymmetric and multimodal probability distributions.
An application of chaos gray-encoded genetic algorithm for Philip infiltration model

Kai-Wen WANG , Xiao-Hua YANG , Yu-Qi LI , Chang-Ming LIU , and Xing-Jian GUO a a Institute of Geographic Sciences and Natural Resources Research, University of Chinese Academy of Sciences, Beijing, China b State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, China c College of Architecture and Landscape Architecture, Peking University, Beijing, China
The Financial Reporting Quality for Commercial Banks - Empirical Evidence in Vietnam

Purpose: The financial reporting quality for enterprises in general and commercial banks in Vietnam in particular plays a very important role because it is used by many stakeholders (internal and external) to make relevant decisions. In this study, the author assessed the current status of financial reporting quality for Vietnamese commercial banks through the qualitative characteristics of financial statements. Theoretical framework: In this study, the author assessed the current status of financial reporting quality for Vietnamese commercial banks through the qualitative characteristics of financial statements according to IASB 2018 including 2 fundamental characteristics including relevance and faithful presentation, 4 enhancing characteristics including understandability, comparability, verifiability, and timeliness. Design/Methodology: The author used a set of measures on the qualitative characteristics of financial statements according to some previous studies in the world. The author collected data from the financial statements from 24 commercial banks in the period of 2019 - 2021. Findings: The research results show that financial reporting quality for Vietnamese commercial banks is not high. Specifically, for the financial reporting quality characteristics according to IASB (2018), the timeliness characteristics were assessed to have the highest value, followed by understandability characteristics. The two enhancing characteristics including relevance and faithful representation of the financial statements for Vietnamese commercial banks were rated as low. The remaining two enhancing characteristics which were the understandability and verifiability characteristics were also rated as low. Research, Practical & Social implication: The study shows The financial reporting quality for enterprises in general and commercial banks in Vietnam in particular plays a very important role because it is used by many stakeholders (internal and external) to make relevant decisions. Originality/ value: The research results will be a useful reference for relevant stakeholders such as the Ministry of Finance, the State Bank of Vietnam, bank managers, shareholders, investors, etc. in management and other related fields.
Understanding the Barriers to Using Locally Grown Wood in the Forest Products Industry

Given the popularity of "buy local" agricultural campaigns, there might be opportunities for Extension to promote the local attribute of wood products. Unfortunately, there is little available literature exploring wood-products manufacturers' attitudes and opinions regarding local wood. In fall 2012, 38 in-depth interviews were conducted with individuals representing a range of firm sizes and final products. Participants provided a definition for what they considered to be local wood and identified four major barriers to the inclusion of Connecticut-grown and -processed wood in their manufacturing: high expense, low visibility, limited demand, and limited availability.
Dynamic State Estimation of Synchronous Machines Using Iterated Square-Root Cubature Kalman Filter and Synchrophasor Measurements

Power system dynamic state estimation is the first prerequisite for control and stability prediction under transient conditions. For a stable and reliable power system, it is crucial and helpful to have accurate, precise, and up-to-date information on the states of the synchronous machines- rotor angle and rotor speed deviation. This paper proposes an application of the Iterated Square-root Cubature Kalman filter (ISCKF) to estimate these main states of synchronous generators. The ISCKF method consists of two step modification - one is the square-root step modification of CKF and the next step is the addition of iterative approach to the square-root CKF method. To demonstrate the performance of the proposed approach during a three-phase short circuit fault, the simulation results, are compared with that of Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF) and Cubature Kalman Filter (CKF). The test systems considered are a single machine infinite bus (SMIB) system, an IEEE 9-bus system and a 19-generator 42-bus test system. The estimation accuracy of the rotor angle using ISCKF method is increased by 6.8–36.54% when compared to that of the CKF method. Similarly, the improvement in accuracy is 4.4–28.57% for estimation of speed deviation.
Comparison of Phytochemical Composition, Antibacterial, and Antifungal Activities of Extracts from Three Organs of Pistacia lentiscus from Saudi Arabia

This in vitro study focused on the antimicrobial activity of methanolic and aqueous extracts of three organs (stems, roots, and leaves) of Pistacia lentiscus against nine bacterial species, two fungal, and one yeast strain. A comparative study of the yield, high-performance liquid chromatography (HPLC) composition, and polyphenol content of the different extracts was conducted. The obtained data showed that the yield of the methanolic extracts (between 13% and 33.3%) was greater than that of the aqueous extracts (between 10% and 18%). The highest yield recorded was in the presence of the methanolic leaf extract, followed by the stem and root extracts. Methanolic extracts are richer in polyphenols than aqueous extracts. Indeed, the highest content was observed in the leaf methanolic extract (28.4 mg GAE/g), followed by the stem (2.96 mg GAE/g), and then the root (2.62 mg GAE/g). HPLC revealed variability in the chemical compositions of the different methanolic extracts. The leaf extract was richer in phenolic acids and flavonoids than the stem and root extracts. Regarding antimicrobial activity, it was concluded that the different methanolic extracts of lentisk were more active than the aqueous extracts. In addition, the different methanolic extracts exhibited antimicrobial activity against all tested strains, despite their morphology and Gram-staining. Indeed, the maximum inhibition zones and the minimum inhibitory concentrations for the bacterial strains sensitive to the different methanolic extracts of the mastic tree were in the range of 7 to 11 mm and 12.5 to 25 µg/mL, respectively. In addition, these extracts showed greater inhibitory activity against the tested fungal strains (A. niger and A. flavus) and yeast (C. albicans) than against the bacterial strains. These extracts can be used to treat antimicrobial infections and as food preservatives.
A Highly Efficient Marine Mammals Classifier Based on a Cross-Covariance Attended Compact Feed-Forward Sequential Memory Network (Student Abstract)

Military active sonar and marine transportation are detrimental to the livelihood of marine mammals and the ecosystem. Early detection and classification of marine mammals using machine learning can help humans to mitigate the harm to marine mammals. This paper proposes a cross-covariance attended compact Feed-Forward Sequential Memory Network (CC-FSMN). The proposed framework shows improved efficiency over multiple convolutional neural network (CNN) backbones. It also maintains a relatively decent performance.
Reconfiguration of the multiwavelength operation of optical fiber ring lasers by the modifiable intra-cavity induced losses of an in-fiber tip probe modal Michelson interferometer

A straightforward and versatile method for switching from single to different multiwavelength laser emission in ring cavity fiber lasers is proposed and demonstrated experimentally. The method is based on using the changeable interference pattern from an optical fiber modal Michelson interferometer as a wavelength selective filter into the ring cavity laser. The interferometer is constructed using a bi-conical tapered fiber and a single-mode fiber segment, with these being spliced together to form an optical fiber tip probe. When the length of the single-mode fiber piece is modified, the phase difference between the interfering modes of the interferometer causes a change in the interferometer free spectral range. As a consequence, the laser intra-cavity losses lead to gain competition, which allows us to adjust the number of simultaneously generated laser lines. A multiwavelength reconfiguration of the laser from one up to a maximum of eight emission lines was obtained, with a maximum SNR of around 47 dBm.
Carbon Nanotube‐Silicone Rubber on Active Thin‐Film Implants

To improve interfacing with neurites, flexible electrode materials consisting of carbon nanotubes (CNTs) and silicone rubber are investigated. Here, the authors present a method for defined application of CNT‐silicone rubber on electrode surfaces. However, for low impedance as well as intimate contact between nerve cells and electrodes, additional reduction of the silicone rubber layer via etching at the interface is necessary. This requires protection of the electrodes using photoresist. The etching methods are optimized for application on ready‐to‐use electrode arrays and characterized using impedance spectroscopy and scanning electron microscopy.
A cross sectional study of Internet addiction among first year medical students

Introduction: With explosive growth in the use of internet world wide India has also seen rapid expansion in the number of internet users with 460 million users according to recent survey. Wi-Fi enabled campuses along with increase in smart phone usage has lead to internet addiction among university students. Aims and Objectives: The present study was conducted to assess the level of internet addiction among first year medical students. Materials and Method: A Questionnaire based Cross sectional study based on Young’s internet addiction scale was conducted among 130 first year medical students belonging to 2016-2017 batch. Results: Mean age of students in the study was 18.07% and average time spent on internet was 2.34hrs/day. 15.4%were found to be average internet users and 61.50% of students fall into the category of possible addicts. 23.10%of students fall into the category of internet addiction. Conclusion: The present study unfolds the dark reality of internet addiction among medical students which requires development of strategies to prevent internet addiction and to prepare a comprehensive program to create awareness and to promote healthy usage of internet. Keywords: Internet addiction, Medical students, Wi-Fi enabled campus, Smart phones, Young’s internet addiction scale
FEM Analysis of Buckled Dielectric Thin-Film Packaging Based on 3D Direct Numerical Simulation

This paper presents a 3D direct numerical simulation of buckled thin-film packaging based on transferred elastic thin-film wrinkling bonded on a compliant polymer ring. The mode change of the fabricated thin-film cap is found by measuring the thin-film cap shape at different times after Si substrate debonding. The conventional linear and nonlinear buckling simulations are not adequate to understand the behavior of the thin-film buckling mechanism creating such packaging cap mode change. Direct buckling simulation is recently reported as an easy and useful numerical wrinkling simulation method. A novel 3D FEM model of a thin-film package suitable for direct 3D buckling simulation is built to reduce the mode mixture between different buckling modes. Buckling modes of the packaging cap are investigated in terms of elastic moduli of package materials and applied strain due to thermal expansion coefficient difference. Based on the simulation results, it is found that there are two main modes in the fabricated thin-film buckling package determining the shape of the transferred thin-film packaging cover depending on the elasticity ratio between the cap and sealing ring materials. The mode shift from wrinkling cap mode to out-of-plane cap mode due to applied strain along a polymeric sealing ring is found.
Simulation Study to Evaluate Full Information Maximum Likelihood as Parameter Estimation Methods for Spatial Vector Autoregressive Model with Calendar Variation

Spatial Vector Autoregressive models with calendar variation can be used to analyze the interrelationships between variables, the relationship of variables with their past and the relationship of variables in a location with those variables in other locations. It also can accommodate the effects of calendar variations. The parameter estimation of this model can be done using Full Information Maximum Likelihood (FIML). The purpose of this study is to evaluate the performance of FIML and it is compared to Ordinary Least Square (OLS) through simulation. The simulation is done using generated data which is designed following Spatial Vector Autoregressive model with calendar variation. There are three aspects studied in this simulation, namely how the effect of error correlation between equations, the variance of error and length of period on the performance of FIML Method and OLS Method. The result of the simulation is the variance of FIML parameter estimator is smaller than OLS, especially when the error correlation between equation are high. While the variance of errors and length of periods have no effect on performance of the estimator. The simulations also show that the mean of parameter estimators both FIML and OLS are very close to the parameters specified.
On the Powerball Method: Variants of Descent Methods for Accelerated Optimization

We propose a new method to accelerate the convergence of optimization algorithms. This method, termed <italic>Powerball method</italic>, simply adds a power coefficient <inline-formula> <tex-math notation="LaTeX">$\gamma \in [0{,}1$ </tex-math></inline-formula>) to the gradient used in various gradient-based optimization schemes. In its essence, the Powerball method can be regarded as the steepest gradient descent with respect to the <inline-formula> <tex-math notation="LaTeX">$p$ </tex-math></inline-formula>-norm, where <inline-formula> <tex-math notation="LaTeX">$p=1+{(}{1}/{\gamma }{)}$ </tex-math></inline-formula>. As a motivation, we first present the continuous-time models of the proposed optimization schemes and analyze their finite-time convergence properties. We then develop several variants of the Powerball method that empirically outperform the standard descent methods, especially during the initial iterations. On multiple real datasets, we demonstrate that the proposed methods can provide a tenfold speedup of the convergence of both (stochastic) gradient descent and limited-memory Broyden–Fletcher–Goldfarb–Shanno (L-BFGS) methods.
REFERENT: Transformer-based Feedback Generation using Assignment Information for Programming Course

Students require feedback on programming assignments to improve their programming skills. An Automated feedback generation (AFG) technique proposes to provide feedback-corrected submissions for incorrect student programming submissions in programming courses. However, these techniques are limited as they rely on the availability of correct submissions as a reference to generate feedback. In situations where correct submissions are not available, they resort to using mutation operators, which can lead to a search space explosion problem. In this work, we propose REFERENT, Transformer-based feedback generation using assignment information. REFERENT uses transfer learning on a pre-trained model with data from students’ submission history from the past assignment. To generate assignment-related feedback, we use a title, tag, assignment description, and test case as assignment information. REFERENT can generate feedback without a reference program in limited resources. We conducted a preliminary study to confirm the effectiveness of REFERENT and the feasibility of using assignment information. REFERENT generated feedback for 32.7% of incorrect submissions without reference programs and that its performance increased up to 50.7% when reference programs were used. We also check whether the submission history, assignment information, and repair knowledge of open-source software help generate feedback.
Quantification of regularity in RR-interval time series using approximate entropy, sample entropy, and multi-scale entropy

QUANTIFICATION OF REGULARITY IN RR-INTERVAL TIME SERIES USING APPROXIMATE ENTROPY, SAMPLE ENTROPY, AND MULTI-SCALE ENTROPY by Nirvish Shah Heart rate variability (HRV) has proven to be a useful noninvasive tool to study the neuronal control of the heart. Recently, nonlinear dynamic methods based on chaos theory and fractal dynamics have been developed to uncover the nonlinear fluctuations in heart rate. Approximate Entropy (ApEn), Sample Entropy (SampEn) and Multi-scale Entropy (MSE) are measures based on chaos theory that quantify the regularity in time series. This study has been designed to examine the ability of these measures to distinguish the RR-interval time series of normal subjects (NSR) from subjects with congestive heart failure (CHF). The study was conducted on the RR-interval data of 44 NSR subjects and 18 CHF subjects. In addition to this, entropy measures of three apparently healthy subjects were calculated during sitting, standing, exercise and paced breathing to determine the change in entropy measures during these conditions. The results showed that ApEn and SampEn measures for 1000 RR-intervals were significantly (P < 0.005) higher for the NSR group than the CHF group. However, no significant difference was observed for these measures calculated for 40,000 RRintervals. MSE analysis revealed that the complexity of the RR-interval time series was significantly higher for the NSR group than the CHF group at all scales but one. SampEn was significantly lower during exercise while there was no significant difference in SampEn for other activities. The results reproduced the findings of others. This study suggests a general decrease in entropy in subjects with congestive heart failure. QUANTIFICATION OF REGULARITY IN RR-INTERVAL TIME SERIES USING APPROXIMATE ENTROPY, SAMPLE ENTROPY, AND MULTI-SCALE ENTROPY