Miracle-dz/UniFAR-FTUs huggingface dataset:
A NEW MATHEMATICAL MODEL FOR THE WORKOVER RIG SCHEDULING PROBLEM

One of the most important activities in the oil and gas industry is the intervention in wells for maintenance services, which is necessary to ensure the constant production of oil. These interventions are carried out by workover rigs. Thus, the Workover Rig Scheduling Problem (WRSP) consists of finding the best schedule to service the wells while considering the limited number of rigs with the objective of minimizing the total production loss. In this study, a 0-1 integer linear programming model capable of effi- ciently solving the WRSP with a homogeneous fleet of rigs is proposed. Computational experiments were carried out using instances based on real cases in Brazil to compare the results obtained by the proposed model with the results reported by other methods. The proposed model was capable of solving all instances considered in a reduced computational time, including the large instances for which only approximate solutions were presently known.
Qualitative and Quantitative Analysis of Nepeta leucostegia Essential Oil Components by GC–MS/FID Along With Antioxidant Activity

Background: Nepeta is a large genus belonging to the Lamiaceae family. So far, no study has been reported on Nepeta leucostegia compounds and biological effects. Objectives: In the present study, we aimed to evaluate the qualitative and quantitative analysis of Nepeta leucostegia essential oil components along with antioxidant activity. Methods: Essential oil compounds of N. leucostegia were qualitatively and quantitatively identified and analyzed using gas chromatography–mass spectrometry (GC-MS) and GC with flame ionization detection (GC-FID) analysis. Besides, the evaluation of the antioxidant property was performed using DPPH assay. Results: After analysis, 96.63% of essential oil compounds were identified. Among the 36 identified compounds, 1,8-cineole (39.1%), epi-α-cadinol (6.9%), α-Terpineol (6.0%), α-fenchene (5.8%), and Camphene (5.5%) were the main compounds, respectively. The essential oil showed a significant antioxidant effect (IC50=75 μg/mL). Conclusion: The results of this study complete the information on the Nepeta genus and can be used in the chemotaxonomic study of the Nepeta genus. Due to its antioxidant effect, N. leucostegia has the potential for use in pharmaceutical and food industries.
DFT investigation of the effect of spin-orbit coupling on the NMR shifts in paramagnetic solids

RP acknowledges financial support from the People Programme (Marie Curie Ac- tions) of the European Union’s Seventh Framework Pro- gramme (FP7/2007-2013) under REA grant agreement n◦ 317127. Via our membership of the U.K.’s HPC Materials Chemistry Consortium, which is funded by EPSRC (n ◦ EP/L000202), this work made use of the facilities of ARCHER, the U.K.’s national high-performance computing service, which is funded by the Office of Science and Technology through EPSRC’s High End Computing Programme. Research was also carried out at the Center for Functional Nanomaterials, Brookhaven National Lab- oratory, which is supported by the U.S. Department of Energy, Office of Basic Energy Sciences, under Contract n◦ DE-AC02-98CH10886.
Disruption of tonic endocannabinoid signalling triggers cellular, behavioural and neuroendocrine responses consistent with a stress response

Endocannabinoid (eCB) signalling gates many aspects of the stress response, including the hypothalamic–pituitary–adrenal (HPA) axis. The HPA axis is controlled by corticotropin releasing hormone (CRH) producing neurons in the paraventricular nucleus of the hypothalamus (PVN). Disruption of eCB signalling increases drive to the HPA axis, but the mechanisms subserving this process are poorly understood.
The multi‐purpose K‐drones general routing problem

In this article, we present and solve the multi‐purpose K$$ K $$ ‐drones general routing problem (MP K$$ K $$ ‐DGRP). In this optimization problem, a fleet of multi‐purpose drones, aerial vehicles that can both make deliveries and conduct sensing activities (e.g., imaging), have to jointly visit a set of nodes to make deliveries and map one or more continuous areas. This problem is motivated by global healthcare applications that deploy multipurpose drones that combine delivery trips with collection of aerial imaging data for use in emergency preparedness and resilience planning. The continuous areas that have to be mapped may correspond to terrain surfaces (e.g., flooded areas or regions with a disease outbreak) or to infrastructure networks to be inspected. The continuous areas can be modeled as a set of lines so that each area is completely serviced if all the lines covering it are traversed. Thus, given a set of nodes and a set of lines, the problem is to design drone routes of shortest total duration traversing the lines and visiting the nodes, while not exceeding the range limit (flight time) and capacity (loading) of the drones. Unlike ground vehicles in classical routing problems, drones can enter a line through any of its points, service only a part of that line and then exit through another of its points. The possibility of flying directly between any two points of the network offered by drones can lead to reduced costs, but it increases the difficulty of the problem. To deal with this problem, the lines are discretized, allowing drones to enter and exit each line only at a finite set of points, thus obtaining an instance of the K$$ K $$ ‐vehicles general routing problem ( K$$ K $$ ‐GRP). We present in this article an integer programming formulation for the K$$ K $$ ‐GRP and propose a matheuristic algorithm and a branch‐and‐cut procedure for its solution. Results are provided for problems with up to 20 deliveries and up to 28 continuous areas.
Experimental investigation of surface morphology of a chemical vapor deposition-grown graphene monolayer mediating with a gap-plasmonic system and the related ripple shape study

We report a method to characterize z-directional surface roughness of chemical vapor deposition-grown graphene monolayers with the aid of surface-enhanced Raman scattering spectral signatures of “out-of-plane” phonon modes observed at Au nanoparticle (NP)–graphene–Au thin film junctions. This method reveals that intensities of the out-of-plane mode (Radial Breathing Like Mode) are strongly correlated with the Full Width at Half Maximum (FWHM) of the de-convoluted 2D peak. On the basis of our findings, in-plane 2D peak shape can be used as a straightforward, quantitative indicator in estimating surface roughness of graphene without loading Au NPs by calculating the FWHM [2D−]/FWHM [2D+] value. Furthermore, we examine the different ripple (RP) shapes on graphene by employing atomic force microscopy-correlated Raman microscopy to identify “threading” and “surrounded” RP types for further investigation on the relationship between spectral features and structural aspects. Electrostatic force microscopy (EFM)-based investigation further substantiates that threading-type RPs in graphene show higher EFM amplitude, indicating that the threading domains tend to be more neutral with a few more sp3 type defects than the surroundings.
Opportunities of measuring hierarchical models of psychopathology

Abstract All psychiatric phenomena are positively associated, and several different models can account for this observation. These include the correlated factors, network, general psychopathology as outcome, and hierarchical models. Advantages of hierarchical models, which consist of one general and several (general factor‐residualized) specific factors, is that the general factor provides an opportunity to reliably measure global distress and impairment, while the specific factors might improve the ability to discriminate between individuals with different kinds of problems. Nevertheless, other models also have their respective advantages, and it remains challenging to empirically determine which model best accounts for the positive manifold in psychiatry. Instead, I present two non‐empirical arguments in favor of hierarchical models. First, by measuring the general factor in isolation, the specific factors tend to include both favorable and unfavorable correlates, which might reduce stigma compared to psychiatric diagnoses that by and large are associated with only unfavorable outcomes. Second, the general psychopathology factor displays an unusual psychometric property in that it includes symptoms of opposite meaning if they have similar valence (e.g., self‐reported symptoms such as gullible and paranoid, lazy and workaholic, and terrified and apathetic load in the same direction), which one might want to measure in isolation from variance capturing the content of symptoms. I conclude by speculating that tests designed based on hierarchical models might help clinical assessment.
Spiraling motion of an underwater glider: Dynamic modeling

An underwater glider is a class of autonomous underwater vehicles. While these gliders typically move in a sawtooth pattern, a spiral motion, which may more effective for specific applications, is considered here. The spiral motion of glider may extend its possible applications such as delivery or recovery equipment for subsea installation. In this paper, a spiral glide path for the glider is considered, and the corresponding dynamic model based on Lagrangian principle and analytical expressions determined. The steady-state spiraling equations were derived and solved recursively using the fsolve algorithm. The results compare well with simulation results based on Newton’s method. The spiraling motion is highly maneuverable, with less than 1 m turning radius.
Using PPO Models to Predict the Value of the BNB Cryptocurrency

This paper identifies hidden patterns between trading volumes and the market value of an asset. Based on open market data, we try to improve the existing corpus of research using new, innovative neural network training methods. Dividing into two independent models, we conducted a comparative analysis between two methods of training Proximal Policy Optimization (PPO) models. The primary difference between the two PPO models is the data. To showcase the drastic differences the PPO model makes in market conditions, one model uses historical data from Binance trading history as a data sample and the trading pair BNB/USDT as a predicted asset. Another model, apart from purely price fluctuations, also draws data on trading volume. That way, we can clearly illustrate what the difference can be if we add additional markers for model training. Using PPO models, the authors conduct a comparative analysis of prediction accuracy, taking the sequence of BNB token values and trading volumes on 15-minute candles as variables. The main research question of this paper is to identify an increase in the accuracy of the PPO model when adding additional variables. The primary research gap that we explore is whether PPO models specifically trained on highly volatile assets can be improved by adding additional markers that are closely linked. In our study, we identified the closest marker, which is a trading volume. The study results show that including additional parameters in the form of trading volume significantly reduces the model's accuracy. The scientific contribution of this research is that it shows in practice that the PPO model does not require additional parameters to form accurately predicting models within the framework of market forecasting. Doi: 10.28991/ESJ-2023-07-04-012 Full Text: PDF
Fabrication and characterization of Pt/Al2O3/Y2O3/In0.53Ga0.47As MOSFETs with low interface trap density

In this work, we fabricated the In0.53Ga0. 47As metal-oxide-semiconductor field-effect-transistors (MOSFETs) with a MOS interface of Y2O3/In0.53Ga0. 47As and recessed gate structure. We investigated the interfacial properties of the gate stack and the junction characteristics of the fabricated MOSFETs. Low subthreshold slope (SS = 110 mV/dec), high on/off current ratio (Ion/Ioff = 106), and high effective mobility of 1600 cm2/V·s were achieved in the MOSFETs at a sheet charge density (Ns) = 1.2 × 1012 cm−2. From the temperature dependence of I–V characteristics, the interface trap density was extracted to be Dit = 2.2 × 1011 cm−2·eV−1 with a negligible trap-assisted leakage current.
Considerations for Mental Health Screening and Referrals: Implications from a School-University Case Study

Abstract School-based mental health screening has been identified as a major component of social, emotional, and behavioral multitiered systems of support models, and a promising practice that can be used to address unmet mental health needs of children and adolescents. However, there are frequently noted concerns about the feasibility of implementing school-based screening programs. In this case study, findings from a school-university partnership, intended to address the most commonly reported screening concerns while reducing screening burdens on the school, are described. Students enrolled in a public middle school in a large, urban city in central Texas completed the self-report version of the Behavioral and Emotional Screening System. Participation in initial school-based screening was high (n = 390), with 35.9% of participants considered at-risk. Screening results informed immediate school-based counseling. However, subsequent screening and comprehensive evaluation for at-risk students—completed at an external university clinic—were low. Implications of these findings, as well as recommendations based on the study methods and related literature, are discussed.
Molecular characterization of Streptococcus agalactiae and Streptococcus dysgalactiae causing bovine mastitis in the southern region of Bangladesh

Objective: This study was conducted to validate polymerase chain reaction (PCR) as a confirmatory diagnostic tool to find out the presence and frequency of Streptococcus agalactiae (S. agalactiae) and Streptococcus dysgalactiae (S. dysgalactiae) in mastitic milk samples obtained from dairy cows in the southern region of Bangladesh. Materials and Methods: A total of 196 samples of bovine milk were collected from various dairy farms in the Chattogram metropolitan area of the southern part of Bangladesh. DNA extracted from isolates obtained by culturing California mastitis test (CMT)-positive mastitic milk samples (n = 146) on 5% sheep blood agar was used as a template for PCR. Two sets of specific primers based on the 16S rRNA gene were used to discriminate between S. agalactiae and S. dysgalactiae. Four PCR products were subjected to sequencing, followed by phylogenetic analysis. Results: The PCR analyses revealed that out of the 146 CMT-positive milk samples tested, 29 samples were positive for S. agalactiae (19.86%), while 26 samples were positive for S. dysgalactiae (17.81%). Further sequence analysis of the corresponding PCR products and bioinformatics analysis verified the results. Conclusion: The study proves the efficiency of PCR as a useful diagnostic approach to determine the presence and prevalence of S. agalactiae and S. dysgalactiae in mastitic milk samples obtained from dairy cows.
An Enhanced Time-Reversal Imaging Algorithm-Driven Sparse Linear Array for Progressive and Quantitative Monitoring of Cracks

A Lamb wave and linear piezoelectric lead zirconate titanate (PZT) array-based monitoring method for the detection and quantification of crack damage is presented in this paper. Because existing PZT array arrangements are not suitable for quantitative monitoring of crack damage both in orientation and in length, a sparse linear PZT array is introduced and applied to collect crack reflections. Based on this new array, a method for estimating crack orientation is proposed. An amplitude spectrum as a function of angle is mapped using time delayed and summed signals. By finding the peaks in the spectra, the central actuator element and corresponding orientation angle are determined. Furthermore, the time of flight imaging method is modified to display and evaluate cracks quantitatively. Validating experiments are conducted on a T6061 aluminum plate, monitoring and evaluating single and connected cracks with various orientations in different locations. As suggested by the experiments, the orientation of most cracks can be well recognized and all cracks can be quantitatively displayed by the proposed methods.
The Effect of Liquidity and Financial Distress on Tax Aggressiveness With Firm Size As The Moderating Variable in State Owned Enterprises (BUMN) Companies Listed on The Indonesian Stock Exchange (IDX) in 2018-2020

Tax aggressiveness is an act of tax planning to minimize the tax expense both legally (tax avoidance) and illegal (tax evasion). This study aims to analyze the effect of liquidity and financial distress on tax aggressiveness with firm size as the moderating variable. The analysis was performed with a Multiple Linear Regression (MLR) and Moderated Regression Analysis (MRA). The population in this study are State Owned Enterprises (BUMN) Companies Listed on The Indonesia Stock Exchange (IDX) in 2018-2020. The sampling technique of this study was using purposive sampling technique. The results show that liquidity had a negative and significant effect on tax aggressiveness. Financial distress had a positive and significant effect on tax aggressiveness. Firm size had no effect on tax aggressiveness. Firm size is able to moderate effect liquidity on tax aggressiveness and firm size is unable to moderate effect financial distress on tax aggressiveness.
A Survey of Passive 3D Reconstruction Methods on the Basis of More than One Image

The research on the 3D scene reconstruction on the basis of its images and video recordings has been in progress for many years. As a~result there is a~number of methods concerning how to manage the reconstruction problem. This article's goal is to present the most important methods of reconstruction including stereo vision, shape from motion, shape from defocus, shape form silhouettes. shape from photo-consistency. All the algorithms explained in this article can be used on images taken with casual cameras in an ordinary illuminated scene (passive methods).
Comparison of intravascular ultrasound, optical coherence tomography, and conventional angiography‐guided percutaneous coronary interventions: A systematic review, network meta‐analysis, and meta‐regression

Intracoronary imaging modalities, including intravascular ultrasound (IVUS) and optical coherence tomography (OCT), provide valuable supplemental data unavailable on coronary angiography (CA) and have shown to improve clinical outcomes. We sought to compare the clinical efficacy of IVUS, OCT, and conventional CA‐guided percutaneous coronary interventions (PCI).
A none-blind deblurring algorithm for noisy images via distributed gradient prior

This paper proposes a none-blind deblurring algorithm for noisy images via distributed gradient prior. The proposed image prior is motivated by observing the gradient properties of noisy images. Based on the prior of image noise's low gradient distribution, we propose an effective optimization method to deal with noisy and blurry images. In this paper, an image-gradient-related distributed factor is introduced to balance image deblurring and denoising. The distributed factor is related to image noise and works adaptively according to different noise levels of blurry images. Richardson-Lucy method is also adopted to achieve a better deconvolution result. Experiments show that our proposed method outperforms other deblurring algorithms in both preserving details and removing noise.
NUMERICAL STUDY OF FLUID FLOW AND HEAT TRANSFER IN TUBE BANKS WITH STREAM-WISE PERIODIC BOUNDARY CONDITIONS

A numerical procedure for the calculation of laminar fully-developed cross-flow and heat transfer in tube-banks heat exchangers is presented. Boundary conditions are introduced in a form similar to the treatment at conventional inlets and outlets. Calculations are performed for in-line square, rotated square and equilateral triangle geometries, with pitch-to-diameter ratio 1.25-2, Reynolds number 101-103 and Pradtl number 1-100, under both constant heat flux and constant wall temperature boundary conditions. Overall pressure drop and heat transfer factors are compared to previous numerical work, empirical correlations and experimental data. Overall pressure drop calculations correlate with experimental data, while at low Reynolds number, heat transfer calculations are shown to depend upon the choice of reference bulk temperature in the rate equation. Graphs of local pressure, drag, and heat transfer coefficients are provided and discussed in detail.
Giant Auxetic Behaviour in Engineered Graphene

Graphene monolayers engineered to adopt a corrugated conformation are found to exhibit very pronounced lateral expansion characteristics upon uniaxial stretching in specific directions, i.e. giant negative Poisson's ratio (auxeticity). Such anomalous properties are manifested in‐plane and may be controlled through the shape and amplitude of the wave‐like pattern of the corrugation, which in the case of graphene may be controlled through the introduction of patterned ‘defects’. This confirms that auxeticity via corrugation can be achieved even at the nanoscale, as demonstrated here for graphene with patterned ‘defects’, suggesting that this mechanism should be operational at different scales of structures, thus providing a new blueprint for the design or manufacture of auxetic materials and metamaterials which can have tailor‐made giant negative Poisson's ratio properties.
TREND ASSESSING USING MANN-KENDALL’S TEST FOR PRIŠTINA METEOROLOGICAL STATION TEMPERATURE AND PRECIPITATION DATA, KOSOVO AND METOHIJA, SERBIA

The study includes statistical analysis of Pristina meteorological station data on temperature and precipitation trends. The data are organized into four time series: average annual air temperatures (Ta), average maximal annual air temperatures (Tamax), average minimal annual air temperatures (Таmin), as well as annual precipitation sums (RRsum), all in the period 1949 – 1999. The Mann-Kendallʹs (MK) trend test analysis of the corresponding hypotheses discloses that the H 0 hypothesis should be accepted. The general conclusion is that there is no trend neither in maximal, minimal, average temperatures, nor in average annual precipitation for the 1949 – 1999 period for the central Kosovo and Metohija (K&M).
Changes of tropical gravity waves and the quasi‐biennial oscillation in storm‐resolving simulations of idealized global warming

Gravity waves generated by tropical deep convection contribute significantly to driving the downward propagation of the quasi‐biennial oscillation (QBO). However, it is currently uncertain how gravity waves and their interaction with the QBO, and thus the QBO itself, will respond to a warming climate. Previous work showed that this uncertainty is a consequence of the parametrization of gravity waves employed in conventional general circulation models. In this study, we therefore perform short explicit simulations of the QBO for different idealized climate states with the model ICON‐A in a deep convection‐permitting set‐up, which means that neither a parametrization of convection nor a parametrization of gravity waves is employed and that the QBO is entirely driven by explicitly resolved waves. Thereby, our simulations allow us to provide a very first direct estimate of how tropical gravity waves and the QBO may change in a warming climate. We found that the gravity wave momentum flux in the lower stratosphere that is relevant for the QBO increases substantially in the warmer climate states and shifts towards faster zonal phase speeds. As a consequence, the downward propagation of the QBO accelerates and the magnitude of the QBO jets in the upper QBO domain increases in the warmer climate states. Thus, our work builds an important first step towards a more comprehensive assessment of potential QBO changes using global storm‐resolving models.