Miracle-dz/UniFAR-FTUs huggingface dataset:
Green Chemistry Assisted Nanoscale Synthesis and Structural Characterization of Some Transition Metal Cations

Nanoparticle studies are groundbreaking today, largely due to unpredictable changes in particle size and surface properties. Therefore, nanoparticles are considered building blocks in optoelectronics, pharmaceuticals, nuclear energy, bioengineering, biomedicine, and industrial applications. Today, the importance of environmentally friendly methods is increasing. The use of the green synthesis method, which adopts an economic synthesis approach that will reduce resource and energy consumption and not harm the environment, is also encouraged in every field. In the study, ascorbic acid, which has biosafety properties, was used as an alternative reagent (agent) to the chemical reduction method. The method process performed with the reagent selected for nanoparticle synthesis has ensured that it is green synthesis, which is adopted as non-toxic and environmentally friendly. In this study, nanoparticles were synthesized by reducing the sulfate, nitrate, chloride, and acetate salts of Cu(II), Ni(II), Co(II), Zn(II), and Mn(II) transition metals with the reducing agent ascorbic acid compound. It is aimed to investigate the effects of the same metal cations and different anion salts on nanoparticle synthesis. Depending on the radius ratios and solubility values of metal cations and anions, the nanoparticle obtained from Ni(CH3COO)2 salt has the smallest radius. Nano metal particles with the largest radius were obtained as a result of reduction from Co(NO3)2 salt. The characterization of the synthesized nanoparticles was recorded by particle size analysis and scanning electron microscopy (SEM) images.
Buckling analysis of thin-walled members via semi-analytical finite strip transfer matrix method

Slender thin-walled members are main components of modern engineering structures, whose buckling behavior has been studied widely. In this article, thin-walled members with simply supported loaded edges can be discretized in the cross-section by semi-analytical finite strip technology. Then, the control equations of the strip elements will be rewritten as the transfer equations by transfer matrix method. This new method, named as semi-analytical finite strip transfer matrix method, expands the advantages of semi-analytical finite strip method and transfer matrix method. This method requires no global stiffness matrix, reduces the size of matrix, and improves the computational efficiency. Compared with finite element method’s results of three different cross-sections under axial force, the method is proved to be reliable and effective.
Multi-Parameter Estimation Method and Closed-Form Solution Study for k-µ Channel Model

This paper proposes a novel multi-parameter estimation algorithm for the k-µ fading channel model to analyze wireless transmission performance in complex time-varying and non-line-of-sight communication scenarios involving moving targets. The proposed estimator offers a mathematically tractable theoretical framework for the application of the k-µ fading channel model in realistic scenarios. Specifically, the algorithm obtains expressions for the moment-generating function of the k-µ fading distribution and eliminates the gamma function using the even-order moment value comparison method. It then obtains two sets of solution models for the moment-generating function at different orders, which enable the estimation of the k and µ parameters using three sets of closed-form solutions. The k and µ parameters are estimated based on received channel data samples generated using the Monte Carlo method to restore the distribution envelope of the received signal. Simulation results show strong agreement between theoretical and estimated values for the closed-form estimated solutions. Additionally, the differences in complexity, accuracy exhibited under different parameter settings, and robustness under decreasing SNR may make the estimators suitable for different practical application scenarios.
Effect of Mobile-Based Counselling on Breastfeeding in Spain: A Randomized Controlled Trial Protocol (COMLACT Study)

Purpose: The primary aim of this study is to determine the influence of an intervention in women based on a free mobile application (LactApp®, Barcelona, Spain) in maintaining breastfeeding (BF) up to 6 months postpartum. The secondary aim is to assess the effect of health literacy (HL) on breastfeeding duration. Methods: A multicenter, randomized controlled clinical trial of parallel groups will be carried out. Women will be randomly assigned to each of the parallel groups. In the control group, usual clinical practice will be followed from the third trimester of pregnancy to promote BF. In the intervention group, and in addition to usual clinical practice, the women will use a free mobile application (LactApp®) from the third trimester to 6 months postpartum. The type of BF at birth, at 15 days and at 3 and 6 months postpartum and the causes of cessation of BF in both groups will be monitored. The hypothesis will be tested using inferential analysis, considering an alpha of 5%. The study protocol was approved by the Clinical Research Ethics Committee of Hospital de la Ribera (Alzira, Valencia, Spain) in February 2021. A per protocol analysis and an intention-to-treat analysis will be performed. Discussion: This study will identify the influence of a mobile application on improving BF rates. If the application proves effective, we will have a tool with free information available to any user at any time of day, which may be complemented by normal clinical practice and be integrated into our health care system. Trial registration: ClinicalTrials.gov ID: NCT05432700.
Monotone Flux Limitation in the Area-preserving Flux-form Advection Algorithm

Abstract The area-preserving flux-form advection algorithm is extended to monotonicity. For this, the nonlinear positive-definite flux limitation of the original approach is replaced by new monotone flux limiters. The monotone fluxes are derived for one-dimensional constant transport velocities. The deformation occurring in divergent flow is accounted for by adding to the monotone advection fluxes a correction term, which has been derived from the deformation of the upstream method. The final algorithm is applicable to arbitrary multidimensional transport problems. However, due to the use of the time-splitting method, it is strictly monotone only in uniform flow fields. Results of different one- and two-dimensional advection experiments are presented, demonstrating that the monotone flux limitation is an attractive alternative to the positive-definite algorithm. Amplitude and phase speed errors are somewhat larger in the monotone advection scheme. The computational effort of the new version is not much la.
Exploring Parental Control and its Impact on Secondary Level Students’ Attitude Towards Studies

In the present study, we examined the relationship between parental controland secondary level students’ attitude towards studies. The population ofthe study was the male and female Secondary level students and theirparents of all the boys’ and girls’ government secondary schools of TehsilSargodha. A sample of 150 students of the10th class and their parents wereselected on an availability basis from the randomly selected 30 secondaryschools including 10 Boys and 20 Girls schools. Two self-developedresearch instruments including one for parents’ control and the other forstudents’ attitude were used. To analyse the data, statistical calculationsincluding frequency, percentage, mean score, standard deviation, t-test,one-way ANOVA and correlation were used. The findings showed that theparents with more public dealing professions tend towards the strict andhighly strict level of parental control and there exist a positive and moderaterelationship between parental control and students’ attitude towards studies.The study recommends that parent teacher regular meetings may beorganized for parents ‘awareness to adopt better control strategy.
CBANet: An End-to-End Cross-Band 2-D Attention Network for Hyperspectral Change Detection in Remote Sensing

As a fundamental task in remote sensing (RS) observation of the earth, change detection (CD) using hyperspectral images (HSI) features high accuracy due to the combination of the rich spectral and spatial information, especially for identifying land-cover variations in bi-temporal HSIs. Relying on the image difference, existing HSI CD methods fail to preserve the spectral characteristics and suffer from high data dimensionality, making them extremely challenging to deal with changing areas of various sizes. To tackle these challenges, we propose a cross-band 2-D self-attention network (CBANet) for end-to-end HSI CD. By embedding a cross-band feature extraction module into a 2-D spatial–spectral self-attention module, CBANet is highly capable of extracting the spectral difference of matching pixels by considering the correlation between adjacent pixels. The CBANet has shown three key advantages: 1) less parameters and high efficiency; 2) high efficacy of extracting representative spectral information from bi-temporal images; and 3) high stability and accuracy for identifying both sparse sporadic changing pixels and large changing areas whilst preserving the edges. Comprehensive experiments on three publicly available datasets have fully validated the efficacy and efficiency of the proposed methodology.
Daytime Hypercapnia Impairs Working Memory in Young and Middle-Aged Patients with Obstructive Sleep Apnea Hypopnea Syndrome

Purpose Obstructive sleep apnea hypopnea syndrome (OSAHS) can lead to cognitive impairment, though few studies have so far examined hypercapnia as its causal mechanism, due to the invasive nature of conventional arterial CO2 measurement. The study aims to investigate the effects of daytime hypercapnia on working memory in young and middle-aged patients with OSAHS. Patients and Methods This prospective study screened 218 patients and eventually recruited 131 patients (aged 25–60 years) with polysomnography (PSG)-diagnosed OSAHS. Using a cut-off of 45mmHg daytime transcutaneous partial pressure of carbon dioxide (PtcCO2), 86 patients were assigned into the normocapnic group and 45 patients into the hypercapnic group. Working memory was evaluated using the Digit Span Backward Test (DSB) and the Cambridge Neuropsychological Test Automated Battery. Results Compared with the normocapnic group, the hypercapnic group performed worse in verbal, visual, and spatial working memory tasks. PtcCO2≥45mmHg was an independent predictor for lower DSB scores (OR=4.057), lower accuracy in the immediate Pattern Recognition Memory (OR=2.600), delayed Pattern Recognition Memory (OR=2.766) and Spatial Recognition Memory (OR=2.722) tasks, lower Spatial Span scores (OR=4.795), and more between errors in the Spatial Working Memory task (OR=2.734 and 2.558, respectively). Notably, PSG indicators of hypoxia and sleep fragmentation did not predict task performance. Conclusion Hypercapnia may be plays an important role in working memory impairment in patients with OSAHS, perhaps more so than hypoxia and sleep fragmentation. Routine CO2 monitoring in these patients could prove of utility in clinical practices.
A Survey on Image Segmentation Using Active Contour and Level Set Method

Image segmentation is a classical and crucial problem in the fields of computer vision and image understanding.This paper gives a review on the variation based active contour model and level set method developed in recent years for image segmentation.The basic ideas of three types of active contour models,i.e.,edge based,region based and edge-region based models,are presented,their advantages and disadvantages are summarized,and a number of improvements are analyzed in detail.The level set method,which is numerically stable and capable of describing the topology change of the contour,is briefly introduced as an advanced numeric algorithm to solve these models.Finally,the potential application of active contour in image registration is discussed.
In Silico and In Vitro Evaluation of Some Amidine Derivatives as Hit Compounds towards Development of Inhibitors against Coronavirus Diseases

Coronaviruses, including SARS-CoV-2, SARS-CoV, MERS-CoV and influenza A virus, require the host proteases to mediate viral entry into cells. Rather than targeting the continuously mutating viral proteins, targeting the conserved host-based entry mechanism could offer advantages. Nafamostat and camostat were discovered as covalent inhibitors of TMPRSS2 protease involved in viral entry. To circumvent their limitations, a reversible inhibitor might be required. Considering nafamostat structure and using pentamidine as a starting point, a small set of structurally diverse rigid analogues were designed and evaluated in silico to guide selection of compounds to be prepared for biological evaluation. Based on the results of in silico study, six compounds were prepared and evaluated in vitro. At the enzyme level, compounds 10–12 triggered potential TMPRSS2 inhibition with low micromolar IC50 concentrations, but they were less effective in cellular assays. Meanwhile, compound 14 did not trigger potential TMPRSS2 inhibition at the enzyme level, but it showed potential cellular activity regarding inhibition of membrane fusion with a low micromolar IC50 value of 10.87 µM, suggesting its action could be mediated by another molecular target. Furthermore, in vitro evaluation showed that compound 14 inhibited pseudovirus entry as well as thrombin and factor Xa. Together, this study presents compound 14 as a hit compound that might serve as a starting point for developing potential viral entry inhibitors with possible application against coronaviruses.
Helical Artifact Reduction Method Using Image Segmentation With CNN Denoising Technique

Helical computed tomography (CT) scans are often performed to obtain three-dimensional images of an object that is longer than the detector. However, the existing quasi-exact and exact reconstruction methods, such as re-binning and Katsevich algorithm, generate interpolation errors or require high computational power. In this work, we propose a method to reconstruct helical CT projections by iteratively reducing helical artifacts. In each iteration, a convolutional neural network (CNN)-based denoising technique is used to accurately segment the prior image (bone and soft tissue image). The results indicate that the proposed algorithm reduces helical artifacts to a significantly greater extent than the existing single slice re-binning (SSR) and weighted filtered backprojection (W-FBP) methods.
A New Species of Branchellion (Hirudinea: Piscicolidae) Parasitizing the Gills of Short-Tail Stingrays (Batoidea: Dasyatidae) from the West Pacific

A new fish leech, Branchellion brevicaudatae sp. n. , is described based on specimens parasitizing the gills of the short-tail stingray, Bathytoshia brevicaudata (Hutton, 1875), collected from Japanese waters. The new species can be distinguished from other congeners by having: i) pulsating vesicles emerging from posterior base of branchiae, one pair per somite; ii) dorsal white spots, not arranged in longitudinal row; and iii) blackish body. A phylogenetic tree based on partial sequences of the mitochondrial cytochrome c oxidase subunit I gene from the new species and other piscicolid worms showed that the new species is sister to Branchellion torpedinis Savigny, 1822. This is the first record of Branchellion Savigny, 1822 from Japanese waters.
RERN: Rich Edge Features Refinement Detection Network for Polycrystalline Solar Cell Defect Segmentation

High-performance defect segmentation techniques are essential for the high-quality manufacturing of polycrystalline solar cells. Edge detection is an effective technique to accurately locate the edge of defects. However, the existing methods ignore global channel information and the representation gap between multiscale features, inhibiting the ability of the network to aggregate discriminative features. In this article, we propose a novel rich edge features refinement detection network consisting of an encoder–decoder structure that captures rich discriminative edge feature representations by interactively exploring global spatial and channel context. To refine the dense global contextual information in the decoding layer, we propose a bidirectional strip refinement attention (BSRA) adaptively capturing long-range spatial dependency with direction information and long-range channel dependency. BSRA is a lightweight and general module that can be easily inserted into the existing edge detection networks with a negligible computational burden. In addition, we release a polycrystalline solar cell defect edge (PSCDE) dataset that is the first high-quality segmentation database to advance the development of high-quality polycrystalline solar cell manufacturing. Our method achieves an ODS F-measure of 0.854 on the PSCDE dataset with strict evaluation criteria (maxDist = 0.0015), outperforming existing state-of-the-art methods. To further verify the generalization ability of BSRA, we apply BSRA to other edge detection networks, and experiments show that the module further improves the accuracy of these methods on PSCDE.
Advanced fingerprint verification software

We have developed a fingerprint software package that can be used in a wide range of applications from law enforcement to public and private security systems, and to personal devices such as laptops, vehicles, and door- locks. The software and processing units are a unique implementation of new and sophisticated algorithms that compete with the current best systems in the world. Development of the software package has been in line with the third generation of our ultrasonic fingerprinting machine1. Solid and robust performance is achieved in the presence of misplaced and low quality fingerprints.
Cellular Response to Bone Morphogenetic Proteins-2 and -7 Covalently Bound to Photocrosslinked Heparin–Diazoresin Multilayer

Despite the plethora of research that exists on recombinant human bone morphogenetic protein-2 and -7 (rhBMP-2 and rhBMP-7) and has been clinically approved, there is still a need to gain information that would allow for their more rational use in bone implantology. The clinical application of supra-physiological dosages of these superactive molecules causes many serious adverse effects. At the cellular level, they play a role in osteogenesis and cellular adhesion, migration, and proliferation around the implant. Therefore, in this work, we investigated the role of the covalent binding of rhBMP-2 and rhBMP-7 separately and in combination with ultrathin multilayers composed of heparin and diazoresin in stem cells. In the first step, we optimized the protein deposition conditions via quartz crystal microbalance (QCM). Then, atomic force microscopy (AFM) and enzyme-linked immunosorbent assay (ELISA) were used to analyze protein–substrate interactions. The effect of the protein binding on the initial cell adhesion, migration, and short-term expression of osteogenesis markers was tested. In the presence of both proteins, cell flattening and adhesion became more prominent, resulting in limited motility. However, the early osteogenic marker expression significantly increased compared to the single protein systems. The presence of single proteins resulted in the elongation of cells, which promoted their migration activity.
Establishment of Highly Efficient Plant Regeneration, Callus Transformation and Analysis of Botrytis cinerea-Responsive PR Promoters in Lilium brownii var. viridulum

Lilium brownii var. viridulum, commonly called Longya lily, is a well-known flower and vegetable plant in China that has poor tolerance to Botrytis fungal disease. The molecularimprovement has mainly been restricted to an efficient regeneration and transformation system. In this study, the highly efficient regeneration of Longya lily was established through the optimization of embryogenic callus, adventitious shoot and rooting induction. The major factors influencing transformation (antibiotics, Agrobacterium concentration, infection time, suspension solution and coculture medium) were examined. The expression responses of PR promoters (ZmPR4 and BjCHI1) to B. cinerea were assessed in transgenic calli. The results showed that Murashige and Skoog (MS) medium with 1.0 mg·L−1 picloram (PIC) and 0.2 mg·L−1 1-naphthaleneacetic acid (NAA) under light conditions and MS with 0.5 mg·L−1 6-benzylaminopurine (6-BA) and 1.0 mg·L−1 NAA under darkness were optimal for embryogenic callus induction (64.67% rate) and proliferation (3.96 coefficient). Callus inoculation into MS containing 2.0 mg·L−1 thidiazuron (TDZ), 0.4 mg·L−1 NAA, 1.0 mg·L−1 TDZ and 0.5 mg·L−1 NAA led to shooting induction (92.22 of rate) and proliferation (3.28 of coefficient) promotion, respectively. The rooting rate reached 99.00% on MS with 0.3 mg·L−1 NAA. Moreover, a transformation rate of 65.56% was achieved by soaking the callus in Agrobacterium at an OD600 of 0.4 for 10 min in modified MS without NH4NO3 as the suspension solution and coculture medium before selecting 75 mg·L−1 hygromycin and 300 mg·L−1 cefotaxime. Only the BjCHI1 promoter was obviously expressed in transgenic calli. These results could facilitate the generation of Longya lily transgenic plants with improved B. cinerea resistance.
Experimental Validation Through a Parallel Computation Algorithm for Evaluation Uncertainty of the Mathematical Model of Direct Expansion Solar Assisted Heat Pump

This paper presents the development of a mathematical model for a direct-expansion solar-assisted heat pump (DX-SAHP) operating in steady-state. The mathematical model was implemented using the scientific software EES and using a code written in Python. It was utilized a lumped parameter model for the heat exchangers and a semi-empirical model for the compressor. The mathematical model was validated using experimental data of a DX-SAHP running with R134a. Two hundred simulations were made combining different correlations for estimating the convective heat transfer coefficient in the evaporator/collector. The Mean Absolute Deviation (MAD) and the Mean Deviation (MD) between the theoretical and experimental values for the COP were 2.6±1.8 % and 0.9±1.8 %, respectively. The MAD and MD between the discharge temperature were 1.56±0.16 % and -1.45±0.16 %. The mean difference between the results using EES and Python were 1.4 %. The use of Python with parallel computing for uncertainty analyses, reduced the simulation time in 88 % if compared with EES. The model in Python is available as open-source through the platform Google Colaboratory.
Spectroscopic analysis of 2-amino-1-naphthalenesulfonic acid, molecular docking, and evaluation of the electronic properties of several solvents

Abstract The spectral properties of 2-amino 1-naphthalene sulfonic acid were investigated using Fourier transform infrared, Raman, and ultra violet-visible techniques as well as density functional theory. Employing the distribution of potential energy, extensive analysis of vibrational spectrum assignments has been performed. Natural bond orbital was used to study the interactions between the donor and acceptor. The molecular electrostatic potential is used to quantify the visual bio-active portions of the molecule. The computed highest occupied molecular orbital and lowest unoccupied molecular orbital values for different solvents indicates the electron stimulation features. Elucidation of localized orbital locator, electron localization function, reduced density gradient, electron-hole distribution analysis, and drug-likeness are also executed. As revealed by molecular docking research, substituents that target amino acids have antiviral action. Graphical Abstract Highlights *Detailed study on structural properties of the title compound is carried out. *Comprehensive spectral analyses, such as FT-IR and FT-Raman, were reported. *HOMO, LUMO energy gap and the molecular electrostatic potential distribution were calculated. NBO and Reduced density Gradient analysis of the title molecule were studied. Biological activity was revealed by molecular docking study.