Miracle-dz/UniFAR-FTUs huggingface dataset:
Interfacial thermal conductance in multilayer graphene/phosphorene heterostructure

Vertical integration of 2D materials has recently appeared as an effective method for the design of novel nano-scale devices. Using non-equilibrium molecular dynamics simulations, we study the interfacial thermal transport property of graphene/phosphorene heterostructures where phosphorene is sandwiched in between graphene. Various modulation techniques are thoroughly explored. We found that the interfacial thermal conductance at the interface of graphene and phosphorene can be enhanced significantly by using vacancy defects, hydrogenation and cross-plane compressive strain. By contrast, the reduction in the interfacial thermal conductance can be achieved by using cross-plane tensile strain. Our results provide important guidelines for manipulating the thermal transport in graphene/phosphorene based-nano-devices.
Lung Surfactant Protein B Peptide Mimics Interact with the Human ACE2 Receptor

Lung surfactant is a complex mixture of phospholipids and surfactant proteins that is produced in alveolar type 2 cells. It prevents lung collapse by reducing surface tension and is involved in innate immunity. Exogenous animal-derived and, more recently, synthetic lung surfactant has shown clinical efficacy in surfactant-deficient premature infants and in critically ill patients with acute respiratory distress syndrome (ARDS), such as those with severe COVID-19 disease. COVID-19 pneumonia is initiated by the binding of the viral receptor-binding domain (RBD) of SARS-CoV-2 to the cellular receptor angiotensin-converting enzyme 2 (ACE2). Inflammation and tissue damage then lead to loss and dysfunction of surface activity that can be relieved by treatment with an exogenous lung surfactant. Surfactant protein B (SP-B) is pivotal for surfactant activity and has anti-inflammatory effects. Here, we study the binding of two synthetic SP-B peptide mimics, Super Mini-B (SMB) and B-YL, to a recombinant human ACE2 receptor protein construct using molecular docking and surface plasmon resonance (SPR) to evaluate their potential as antiviral drugs. The SPR measurements confirmed that both the SMB and B-YL peptides bind to the rhACE2 receptor with affinities like that of the viral RBD–ACE2 complex. These findings suggest that synthetic lung surfactant peptide mimics can act as competitive inhibitors of the binding of viral RBD to the ACE2 receptor.
Multi-valued Signalling for High E-ciency Optical Communication Systems

This thesis examines the use of multi-valued signalling to increase the performance of optical communication systems. First, comparing 4-ary ASK to binary OOK, we evaluated that 4-ary ASK has an inherent back to back receiver sensitivity penalty of 3.8 dB to 7.1 dB, depending on the pulse coding used. In the analysis, nonreturn to zero and return to zero coded pulses were included. Moreover 4-ary ASK is more tolerant to system dispersion, having wider 1-dB dispersion width as compared to OOK. The effect of the nonlinear Kerr effect was also examined. Self phase modulation (SPM) imposes its effect at a larger average received power for 4-ary ASK as compared to binary OOK. We explain this by considering that OOK pulses are twice as fast, which affects the nonlinear frequency chirp imposed on them by the SPM effect. However, the initial penalty does not allow any clear advantage of multilevel signalling in the single channel case. However, the increased tolerance to dispersion allows the diffusion of the nonlinear Kerr effect in the case of cross phase modulation (XPM). Cases where OOK systems were limited due to XPM exhibited an acceptable performance under 4-ary ASK. Considering dispersion and the walk-off effect alone the maximum obtainable spectral efficiency was proved not to be affected. Simulation work for a system with 0.66 bits/s/Hz spectral efficiency and 9 channels showed that the initial penalty is substantially reduced, which is ought to the use of higher optical filtering. 3 Finally, we derived the moment generated function for the decision variable of a delay demodulated, differentially detected DQPSK system. Using the saddlepoint approximation we evaluated the BER. Thus the relative performance of DQPSK and DPSK systems was compared. The effects of optical filtering, source linewidth, optical signal to noise ratio and system dispersion were included in the model.
Application of the Quantum Learning Model in Increasing Adolescent Happiness

Period teenager is period which urgent within range life, because is period something period transition, a time of change, a troubled age, a moment where individual look for identity, age which raises Fright, period which no realistic, and as threshold adulthood. Based on the stages of its development, adolescence is called a transitional period because it is experiencing physiological development, emotional development and social development which will cause fear, anxiety and even self-doubt. Happiness depends on how young people keep themselves in a condition to make the best use of our energy. Teenagers should feel happy at school and learning with teachers in class. Teacher BK / Counselor is wrong one educator which role in help students overcome obstacles or problems and develop potency which owned student in school including student happiness. One learning model that can increase student happiness in class is the quantum learning model. the Quantum learning model seeks to maximize all the elements contained in learning including all the potential and abilities that exist in students. This is intended to make the learning carried out by the teacher maximal and students also absorb the material presented maximally. The current research is descriptive qualitative with a literature study that seeks to provide an overview of the application of the Quantum learning model to increase adolescent happiness. This paper presents the problem of adolescent happiness at school, steps to apply the Quantum learning model and increase adolescent happiness at school. This research uses literature study / literature study, by reviewing several research results, articles, books and case studies that occur in the field.
Social networks addictions and academic performance of students at the University of Kinshasa

This study is part of the policy of preventing addictive behaviors in the academic environment in order to ensure the integral well-being of students. Its aim was to relate social network addiction to the academic performance of students at the University of Kinshasa. To this end, a social network addiction test was administered to a sample of 91 graduate students from several faculties at the University of Kinshasa. This test was coupled with a documentary technique that provided us with the students' academic performance at the end of the 2020-2021 academic year. The social network addiction test divided the sample into two groups: (1) social network addicts (23 subjects or 25.3%) and (2) social network non-addicts (68 subjects or 74.7%). In terms of academic performance, three student profiles emerged: (1) 57 students or 62.6% of subjects demonstrated average quality achievement (60-69%); (2) 30 students or 33% of subjects demonstrated low quality achievement (50-59%), (3) 4 students or 4.4% of subjects demonstrated higher quality achievement. Comparing the academic grades of subjects addicted to social networking with those of non-addicts, a statistically significant difference was found. The non-addicts performed better academically than the addicts. Thus, we can conclude that addiction to social networks negatively affects the performance of understudy students. These results can serve as a basis for raising students' awareness of the dangers of abusing social networks. They can help in any attempts to regulate the use of telephones in the academic environment. Last but not least, they can be used as a frame of reference for the University's policy on addiction prevention.
Traversable Region Detection and Tracking for a Sparse 3D Laser Scanner for Off-Road Environments Using Range Images

This study proposes a method for detecting and tracking traversable regions in off-road conditions for unmanned ground vehicles (UGVs). Off-road conditions, such as rough terrain or fields, present significant challenges for UGV navigation, and detecting and tracking traversable regions is essential to ensure safe and efficient operation. Using a 3D laser scanner and range-image-based approach, a method is proposed for detecting traversable regions under off-road conditions; this is followed by a Bayesian fusion algorithm for tracking the traversable regions in consecutive frames. Our range-image-based traversable-region-detection approach enables efficient processing of point cloud data from a 3D laser scanner, allowing the identification of traversable areas that are safe for the unmanned ground vehicle to drive on. The effectiveness of the proposed method was demonstrated using real-world data collected during UGV operations on rough terrain, highlighting its potential as a solution for improving UGV navigation capabilities in challenging environments.
Approximation of common fixed points of left Bregman strongly nonexpansive mappings and solutions of equilibrium problems

Abstract In this paper we propose an iterative algorithm based on the hybrid method in mathematical programming for approximating a common fixed point of an infinite family of left Bregman strongly nonexpansive mappings which also solves a finite system of equilibrium problems in a reflexive real Banach space. We further prove that our iterative sequence converges strongly to a common fixed point of an infinite family of left Bregman strongly nonexpansive mappings which is also a common solution to a finite system of equilibrium problems. Our result extends many recent and important results in the literature.
Single Precision in Weather Forecasting Models: An Evaluation with the IFS

AbstractEarth’s climate is a nonlinear dynamical system with scale-dependent Lyapunov exponents. As such, an important theoretical question for modeling weather and climate is how much real information is carried in a model’s physical variables as a function of scale and variable type. Answering this question is of crucial practical importance given that the development of weather and climate models is strongly constrained by available supercomputer power. As a starting point for answering this question, the impact of limiting almost all real-number variables in the forecasting mode of ECMWF Integrated Forecast System (IFS) from 64 to 32 bits is investigated. Results for annual integrations and medium-range ensemble forecasts indicate no noticeable reduction in accuracy, and an average gain in computational efficiency by approximately 40%. This study provides the motivation for more scale-selective reductions in numerical precision.
Fatigue crack monitoring of aerospace structure based on binary tree support vector machines

This paper presents a novel method to monitor crack length which based on binary tree support vector machines (BTSVM). In this method, matching pursuit method with Chirplet atom is applied to extract the matching parameters as feature vectors to train and test in the BT-SVM algorithm. Then one simulation of lug joint is carried out for studying the effect of crack extension on Lamb wave signals propagation. Fatigue loading experiments on lug joints are carried out at last. The results show that this new method can monitor the length of fatigue crack effectively.
Effects of whole-plant corn and hairy vetch (Vicia villosa Roth) mixture on silage quality and microbial communities

Objective Hairy vetch is considered to improve the nutritional value of corn because of its high protein and mineral levels. To better understand the mechanism underlying hairy vetch regulated whole-plant corn silage fermentation, this experiment investigated the fermentation quality and bacterial community of whole-plant corn and hairy vetch mixture. Methods Whole-plant corn and hairy vetch were mixed at ratios of 10:0 (Mix 10:0), 8:2 (Mix 8:2), 6:4 (Mix 6:4), 4:6 (Mix 4:6), 2:8 (Mix 2:8), and 0:10 (Mix 0:10) on a fresh weight basis. After ensiling 60 days, samples were collected to examine the fermentation dynamics, ensiling characteristics, and bacterial communities. Results Mix 0:10, Mix 2:8, and Mix 4:6 showed poor fermentation characteristics. Mix 8:2 and Mix 6:4 silages showed high quality, based on the low pH, acetic acid, and ammonia nitrogen levels and the high lactic acid, crude protein, and crude fat contents. The bacterial diversity was affected by the mixing ratio of the two forage species. The genus Lactobacillus dominated the bacterial community in Mix 10:0 silage, whereas with the addition of hairy vetch, the relative abundance of unclassified-Enterobacter increased from 7.67% to 41.84%, and the abundance of Lactobacillus decreased from 50.66% to 13.76%. Conclusion The silage quality of whole-plant corn can be improved with inclusion levels of hairy vetch from 20% to 40%.
Geometric Studies on the Class U(λ)

The article deals with the family U( ) of all functions f normal- ized and analytic in the unit disk such that z=f(z) 2 f 0 (z) 1 < for some 0 < 1. The family U( ) has been studied extensively in the recent past and functions in this family are known to be univalent in D. However, the prob- lem of determining sharp bounds for the second coecients of functions in this family was solved recently by Vasudevarao and Yanagihara but the proof was complicated. In this article, we rst present a simpler proof of it. We obtain a number of new subordination results for this family and their consequences. Also, we obtain sharp estimate for the classical Fekete-Szego inequality for functions in U( ). In addition, we show that the family U( ) is preserved under a number of elementary transformations such as rotation, conjugation, dilation and omitted value transformations, but surprisingly this family is not preserved under the n-th root transformation for any n 2. This is a basic here which helps to generate a number of new theorems and in particular provides a way for constructions of functions from the familyU( ). Finally, we deal with a radius problem and the paper ends with a coecient conjecture.
Edaravone Exerts Protective Effects on Mice Intestinal Injury without Interfering with the Anti-Tumor Effects of Radiation

The appropriate dosage of edaravone—a radioprotective agent—and its effect on tumors are unknown. This study evaluated the effects of edaravone on intestinal injuries and tumors in mice induced by whole body X-ray irradiation. Small intestinal mucositis was induced in C3H/HeNSlc mice using a single X-ray dose (15 Gy). Edaravone (15, 30, and 100 mg/kg) was administered 30 min before irradiation to evaluate its protective effect. After 3.5 days, the jejunum was removed and the histological changes were evaluated. Next, C3H/HeNSlc mice with squamous cell carcinoma VII tumors were provided the same single X-ray dose and 100 mg/kg edaravone; further, the tumors were immediately induced after irradiation. The tumor cell viability was detected using an in vivo–in vitro colony formation assay. We found that the intestinal colony-forming ability after irradiation was significantly higher in the 100 mg/kg edaravone group than that in the control group. Moreover, the apoptotic cells in the villi immunohistochemically stained with cleaved caspase-3 were significantly lower in the 100 mg/kg edaravone group than in the control group. We found no radioprotective effects of intraperitoneally inoculated edaravone in both hind legs on squamous cell carcinoma VII tumors. These findings suggest that 100 mg/kg edaravone exerts protective effects on small intestinal injuries without interfering with the antitumor effects of radiation.
Low-order modelling for feedback control of fluid flows around complex geometries

The majority of goods transportation vehicles' power is consumed in overcoming aerodynamic drag which arises due to vortex shedding over the bluff rear end of the vehicle. As such, a reduction in pressure drag via feedback control could have significant economic and environmental effects on CO2 emissions, as well as reducing fatigue acting on the body. The difficulty in designing such controllers lies in obtaining models suited to modern control design methods, which are necessarily of much lesser complexity than typical Computational Fluid Dynamics models, or models derived from immediate spatial discretisation of the equations governing fluid flows. It is with obtaining such low-order models that the work presented in this thesis is concerned. A computationally efficient modelling approach which is suited to obtaining low- order models of complex geometry fluid flows is described, whereby the system's overall input-output frequency response is built up by connecting together the frequency responses of a large number of computational node subsystems in an efficient manner, exploiting the inherent structure of spatially discretised PDAEs. In order to choose a suitable formulation of the governing equations – the Navier- Stokes equations – a rigorous analysis of several of the formulations suggested in the literature is presented, whereby the dynamics of different formulations are compared both at the nodal level, and at the full system level for a 2D channel flow (for which a well studied benchmark model exists). In the penultimate chapter, the work of previous chapters is consolidated by apply- ing the modelling technique to a 2D backward facing step flow. Slot jet actuation on the rear edge is assumed, and two separate output configurations are considered. The resulting models are compared to models obtained in a computational system iden- tification study, which prompts an interesting investigation into the dynamics of the common PISO Computational Fluid Dynamics algorithm.
Bayesian Estimation for White Light Interferometry

In this thesis, a new approach for the reconstruction of height maps from scanning white light interferometry is presented. This method unifies the conventional steps of pre- and postprocessing within Bayesian inference. An adept formulation of the prior allows for the exact computation of the height estimate, obviating the need for stochastic sampling or simulation methods. In conventional surface estimation for white light interferometry, a primary height map is calculated pixel-wise from the raw data, followed by a postprocessing step where outliers and other measurement artifacts are removed. Established and novel algorithms for both steps are discussed. The techniques of Bayesian inference for 2-D image processing, on which the novel surface estimation approach bases, are presented afterwards. For this new method, the localization of the fringe pattern is represented by the likelihood function, while the knowledge about the general surface properties goes into the prior probability of local height configurations. Both the 3-D data set and this prior are considered simultaneously in the estimation procedure, which analytically yields the optimum surface reconstruction as a mode of the marginal posterior probability. A method for quantitative comparison of height maps is developed and used to assess the performance of different postprocessing algorithms.
Distributional Mellin calculus in $\mathbb{C}^n$, with applications to option pricing

We discuss several aspects of Mellin transform, including distributional Mellin transform and inversion of multiple Mellin-Barnes integrals in $\mathbb{C}^n$ and its connection to residue expansion or evaluation of Laplace integrals. These mathematical concepts are demonstrated on several option-pricing models. This includes European option models such as Black-Scholes or fractional-diffusion models, as well as evaluation of quantities related to the optimal exercise price of American options.
Outer Lain sands of Typhoons

Some features of the outer rain bands of typhoons are studied. A schematical illustration of surface pressure pattern in a typhoon is presented through the analysis of weather elements. It is shown from the radar echo analysis that the velocity of precipitation cells in rain bands is approximately equal to the resultant velocity of typhoon system and gradient wind, and that this fact may be used for the prognosis of movement of typhoons.
Floor-Mounted Robotic Pedicle Screw Placement in Lumbar Spine Surgery: An Analysis of 1,050 Screws

Objective To analyze the usage of floor-mounted robot in minimally invasive lumbar fusion. Methods Patients who underwent minimally invasive lumbar fusion for degenerative pathology using floor-mounted robot (ExcelsiusGPS) were included. Pedicle screw accuracy, proximal level violation rate, pedicle screw size, screw-related complications, and robot abandonment rate were analyzed. Results Two hundred twenty-nine patients were included. Most surgeries were primary single-level fusion. Sixty-five percent of surgeries had intraoperative computed tomography (CT) workflow, 35% had preoperative CT workflow. Sixty-six percent were transforaminal lumbar interbody fusion, 16% were lateral, 8% were anterior, and 10% were a combined approach. A total of 1,050 screws were placed with robotic assistance (85% in prone position, 15% in lateral position). Postoperative CT scan was available for 80 patients (419 screws). Overall pedicle screw accuracy rate was 96.4% (prone, 96.7%; lateral, 94.2%; primary, 96.7%; revision, 95.3%). Overall poor screw placement rate was 2.8% (prone, 2.7%; lateral, 3.8%; primary, 2.7%; revision, 3.5%). Overall proximal facet and endplate violation rates were 0.4% and 0.9%. Average diameter and length of pedicle screws were 7.1 mm and 47.7 mm. Screw revision had to be done for 1 screw (0.1%). Use of the robot had to be aborted in 2 cases (0.8%). Conclusion Usage of floor-mounted robotics for the placement of lumbar pedicle screws leads to excellent accuracy, large screw size, and negligible screw-related complications. It does so for screw placement in prone/lateral position and primary/revision surgery alike with negligible robot abandonment rates.
Influence of dry season on social wasp communities (Hymenoptera: Polistinae) in Deciduous Forest

The seasonal deciduous forest, also known as dry forest, is characterized by the deciduity of tree species and two well-defined seasons which cause drastic changes in its physiognomy, and the seasonality of rainy periods directly impacts the forest’s biological communities. Social wasps (Vespidae: Polistinae) are well documented. However, some ecosystems in which they occur, such as the deciduous forest, are still subsampled. This study aimed to assess the response of social wasp communities to the dry season in a deciduous forest in the Mata Seca State Park, in the North of the state of Minas Gerais, Brazil. Insects were collected over 24 days divided into four field campaigns, each with six continuous days of collection (February, May, July, and November 2021), encompassing one campaign per season. All specimens were sacrificed and stored in 70% alcohol and later dry mounted for identification. The Kruskal-Wallis (KW) H test was performed to verify the difference between species richness, number of total colonies, and number of colonies of each tribe in relation to the collection station. In total, 131 colonies of eight species were located, particularly Polybia occidentalis (Olivier, 179), with 39 colonies, Polistes versicolor (Olivier, 1791), with 33, Mischocyttarus cassununga, with 21, and Protonectarina sylveirae (Saussure, 1854), with 13. Six species, five of which were from the Epiponini tribe, were collected in the four seasons. The responses of social wasps to the periods of drought in the deciduous forest vary with tribe. While Epiponini populations can keep colonies active in the dry season, Polistini cannot. Meanwhile, P. versicolor responds positively to the onset of the rainy season, increasing its population.