Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigations of electron wave-packet dynamics and high-order harmonic generation in laser-aligned molecules

Abstract We review recent work examining electron dynamics and high-order harmonic generation (HHG) in molecules exposed to high intensity (1013−1015 W cm−2) ultrashort pulse laser fields. The use of adiabatic laser alignment techniques, using relatively long duration (300 ps) laser pulses of moderately high intensity (1011-1012 W cm−2) enabled us to perform the first experiments investigating the role of the angle between the laser polarization vector and the molecular axis. We have shown that alignment of a sample can enhance the harmonic yield by a small but significant factor. HHG in model H2 and H+ 2 molecules was treated theoretically by numerical integration of the Schrödinger equation. The unique influence of the dipole phase in molecular HHG is clearly demonstrated and is shown to offer a consistent explanation for our experimental observations. The electron wavepacket dynamics exhibit strong interference effects that result in the reduction or enhancement of harmonic yield at certain alignment angles. Experiments to further investigate these effects and to increase the modulation of the harmonics by molecular alignment are discussed.
Applying Satellite Gradient Moisture Information to Local-Scale Water Vapor Analysis Using Variational Methods.

Abstract Horizontal shape matching (HSM) is a variational technique used to obtain an analysis that merges the gradient structure from one data source (e.g., satellite) with a background field. This technique is modeled after the variational methods that fall into two general categories: strong constraint and weak constraint. HSM, which is essentially a specialized filter function, falls in the weak constraint category. Here a technique is demonstrated that effectively tunes the filter to the spatial resolution inherent in the data sources rather than on the absolute error of the data. The HSM equation is developed for satellite gradient insertion including a cloud treatment. The filtering properties of the HSM equation are explored using Fourier analysis, and an approximate numerical solution is shown to be viable for operational use. Applying this technique to a dataset spanning more than a year proves the analysis has a positive effect through the statistical significance of a large sample of compariso.
Wavelet-based empirical Wiener filtering

Existing denoising schemes rarely use multiple-bases representations and if they do, they do not address the choice of the different bases. We present a new denoising scheme based on multiple bases processing. The multiple bases used in the denoising algorithm are generated via unitary transforms. These unitary transforms also allow the construction of new wavelet bases. In the new domains spanned by the multiple bases, we apply a simple hard thresholding technique as well as a more complex Wiener filtering scheme. Preliminary results suggest that the resulting algorithms can deliver significantly improved performance over the undecimated wavelet transform without being computationally more expensive.
A Geometric-Feature-Based Method for Automatic Extraction of Anchor Rod Points from Dense Point Cloud

As the technology of high-precision 3D laser scanning becomes increasingly prevalent in the fields of hydraulic building modeling and deformation monitoring, the quality of point clouds plays an increasingly crucial role in data processing. This paper investigates an automatic extraction method of anchor rod points based on geometric features, which focuses on the influence of anchor rod points and mixed pixels in the data of an underground powerhouse of a pumped storage power station on modeling and deformation monitoring during the construction period. This workflow consists of two steps that can automatically extract anchor rod points from high-density point cloud data. Triangular mesh features in the local neighborhood and the parameters of the anchor rods are used to locate the anchor rod in downsampled data, and curvature features are used to extract anchor rod points precisely. The experiment of extracting anchor rods shows that the accuracy of this method of initial identification is 97.2%. Furthermore, precise extraction based on curvature curve fitting is applicable. This method can accurately separate the three types of anchor rods from the dense point cloud on the rough surface of a cavern roof; the false-extraction rate of anchor rod points is about 0.11% to 5.09%. This method can provide high-quality and dependable data sources for the precise registration, modeling and deformation analysis of point clouds in a construction cavern.
Influences of Emotional Information on Response Inhibition in Gaming Disorder: Behavioral and ERP Evidence from Go/Nogo Task

Background: Gaming disorder (GD) may impair executive functions such as response inhibition. According to the tripartite neurocognitive model, the interoceptive system generates a state of craving that exacerbates the dysfunction of GD. We speculate that emotional information may play an important role in the mechanism, which leads to impaired response inhibition in people with GD. Methods: A three-factor mixed experimental design was adopted in this go/nogo task. The between-subject factor was group (GD or control group), and the within-subject factors were two types of emotional information, task relevance (related or unrelated) and emotional valence (negative or positive). Results: The GD group had lower nogo accuracies than the control group in the task-unrelated condition and also in the negative condition. Parallelly, the GD group showed faster reactions and lower accuracy in the go trials than the control group under task-unrelated negative conditions. At the neural level, the GD group had smaller amplitudes of nogo-N2 and larger amplitudes of nogo-P3 than the control group in the task-unrelated condition. Conclusions: The findings prove the hypothesis of this study that emotional information could be a factor leading to impaired response inhibition in GD individuals. The response inhibition abilities of GD are weakened when processing task-unrelated or negative information, which may be caused by failure of behavioral inhibition and weakened conflict control, resulting in more cognitive resources to complete response suppression under specific conditions. This study provides evidence for weaker response inhibition in GD individuals from the perspective of cognitive–emotional interaction and provides more detailed information for interventions for GD.
Comparison of tests for bivariate normality with unknown parameters by transformation to an univariate statistic

Fifteen tests for bivariate normality with unknown parameters have been compared. A Monte Carlo power analysis with componently independent uniform, lognormal and Student t4 distributions and with members of the family of bivariate gamma distributions as alternative hypothesis has been carried out. The Shapiro-Wilk- Stephens test has been found to perform well for all alternative distributions analyzed. The Shapiro-Wilk- Malkovich and Malkovich bl tests exhibit good power against the lognormal and the family of bivariate gamma distributions, but show poor power against independent uniform distributions. The bivariate test methods have been illustrated for the strength and elongation at break of Dyneema polyethylene yarn and nylon 6 monofilament. Dyneema is a trademark of DSM.
Stability of defects in lead–zirconate–titanate after unipolar fatigue

Bipolar fatigue in ferroelectric lead–zirconate–titanate was previously shown to induce stable pinning centers for ferroelectric domain walls resulting in a significant loss in switchable polarization, but only fairly weak offsets were induced. The corresponding scenario after unipolar fatigue is reversed inducing fairly stable offsets while hardly any loss in domain mobility is encountered. The charged defects inducing the offsets are suggested to be located at grain boundaries, while pinning centers reducing domain wall mobility predominantly reside within the grain.
Semiclassical treatment of nonadiabatic transitions: Multilevel curve crossing and nonadiabatic tunneling problems

Nonadiabatic transition in a multilevel curve crossing system and the one accompanying quantum mechanical tunneling are investigated theoretically and numerically for the one‐dimensional case. The first problem is analyzed using the semiclassical formulation based on the sophisticated two‐state theory for nonadiabatic transition. This formulation is applied to three‐ and four‐level model systems and is found to work surprisingly well even when the avoided crossings (or the transition zones) cannot be regarded to be well separated. The significance of the Stokes phase is noticed. As for the second problem, analysis is made not only for the simple tunneling but also for the elastic scattering accompanied by the nonadiabatic tunneling. A combination of the following two formulas is recommended for practical use: (1) the formula essentially based on the one proposed by Coveney et al., and (2) the formula of Ovchinnikova with additional Stokes phase and tunneling corrections.
Automated Generation of Meeting Minutes using Deep Learning Techniques

: Meeting minutes are important to keep track of key decisions and agreements that were made during a meeting. It is crucial to document the topics discussed and the decisions made so they can be reviewed at the beginning of the next meeting as well as for future reference. Many companies while conducting meetings, keep paid employees to note down meeting minutes taking up valued time and resources. We o ff er a solution to make better use of available tools and technological advancements to help employees conduct e ff ective discussions to boost a company’s productivity. Automated Minute Book Creation (AMBOC) uses machine learning to derive key information from important discussions. AMBOC is an automated system to create transcripts and minutes of a meeting with the added advantage of speaker recognition. The model we propose will be capable of transforming an audio file into plain-text using Deep Neural Networks (DNN), recognizing the speaker using Mel Frequency Cepstral Co-e ffi cient (MFCC) as well as summarizing the meeting transcript into condensed minutes with the help of Transformers.
Sensory Perturbations from Hindlimb Cutaneous Afferents Generate Coordinated Functional Responses in All Four Limbs during Locomotion in Intact Cats

Abstract Coordinating the four limbs is an important feature of terrestrial mammalian locomotion. When the foot dorsum contacts an obstacle, cutaneous mechanoreceptors send afferent signals to the spinal cord to elicit coordinated reflex responses in the four limbs to ensure dynamic balance and forward progression. To determine how the locomotor pattern of all four limbs changes in response to a sensory perturbation evoked by activating cutaneous afferents from one hindlimb, we electrically stimulated the superficial peroneal (SP) nerve with a relatively long train at four different phases (mid-stance, stance-to-swing transition, mid-swing, and swing-to-stance transition) of the hindlimb cycle in seven adult cats. The largest functional effects of the stimulation were found at mid-swing and at the stance-to-swing transition with several changes in the ipsilateral hindlimb, such as increased activity in muscles that flex the knee and hip joints, increased joint flexion and toe height, increased stride/step lengths and increased swing duration. We also observed several changes in support periods to shift support from the stimulated hindlimb to the other three limbs. The same stimulation applied at mid-stance and the swing-to-stance transition produced more subtle changes in the pattern. We observed no changes in stride and step lengths in the ipsilateral hindlimb with stimulation in these phases. We did observe some slightly greater flexions at the knee and ankle joints with stimulation at mid-stance and a reduction in double support periods and increase in triple support. Our results show that correcting or preventing stumbling involves functional contributions from all four limbs.
Modeling Incomplete Scaled Questionnaire Data with a Partial Credit Hierarchical Measurement Model

The partial credit hierarchical measurement model (HMM) results when a partial credit IRT model and a hierarchical linear model are combined (Bryk & Raudenbush, 1992; Masters, 1982). This combined model enables the standard errors of parameters to be estimated accurately. The partial credit HMM is illustrated using a subset of data from the Sloan Study of Youth and Social Development, a five-year longitudinal project studying the career aspirations of adolescents. The data used for this study consisted of a subset of students’ responses to multiple administrations of an attitudinal questionnaire, as well as student-level covariates. Using student responses to seven seven-point semantic differential items tapping student mood, the partial credit HMM was used to explore the effects of gender and classroom activity upon student mood as students were engaged in a mathematics classroom. Gibbs sampling and the Metropolis-Hastings algorithm were used to impute values for the missing data and to estimate the parameters of the model. The results of the data analysis indicated that female students had lower mood than male students did for all classroom activities.
Characterization and evaluation of multiple biological activities of phytosynthesized gold nanoparticles using aqueous extract of Euphorbia dendroides

Novel metallic nanoparticles (NPs), such as biosynthesized gold nanoparticles (AuNPs), have been extensively studied because of their wide applications. Consequently, the present investigation aimed at the biosynthesis, characterization, and comparative assessment of biological activities of AuNPs. Biosynthesized AuNPs (ED-AuNPs) were synthesized using aqueous extract of Euphorbia dendroides (E. dendroides) aerial parts (EDAE), which functions as a reducing and stabilizing agent by its nature. Presence of tannins, saponins, flavonoids, alkaloids, glycosides/or carbohydrates, steroids, and terpenes was revealed by the qualitative phytochemical analysis of EDAE. Characterization of the biosynthesized AuNPs was attained by UV-Visible spectrophotometry, transmission electron microscopy (TEM), XRD, and Fourier transform infrared (FTIR). The cytotoxic effects of ED-AuNPs and EDAE were assessed in vitro against HepG2 and HCT-116 cancer cells. The MTT assay revealed a significant cytotoxic effect of ED-AuNPs and EDAE on HepG2 (IC50 = 41.72 ± 1.26 and 55.26 ± 2.25 μg mL−1) as well as HCT-116 (IC50 = 44.96 ± 3.23 and 69.83 ± 0.96 μg mL−1) cells, thus indicating their potential anticancer activity. Furthermore, ED-AuNPs exhibited potent anti-diabetic activity, with an IC50 value of 19.8 ± 1.97 µg mL−1, pointing to their plausible use as therapeutics in the treatment of diabetes, as well as a promising antimicrobial activity against H. pylori.
On a relationship between the convergents of the nearest integer and regular continued fractions

In this paper we derive a relation concerning the speed of convergence of the nearest integer and regular continued fractions. If AnIBn, Pklqk denote the convergents of the nearest integer and regular continued fractions of an irrational number a. , then for all n there is a k(n) such that An=Bn = Pk(n)lqk(n). It is shown that /1 +/5 log( 2 n 2 lim n-) k(n) log 2 for almost all a. This problem is reduced to a special case of a general result concerning the frequency of partial quotients in the regular continued fraction (Theorem 2).
Enhancing employee performance through the application of dispute resolutions in the banking industry

This study examined the effect of dispute resolution strategies on employee performance in the Nigerian banking industry. Two variables were discussed; compromising strategy and integrating strategies as they affect employee performance in selected banks in Delta State. The sample size for the study was 162 respondents. A simple random sampling technique was adopted. Validated structured sets of questionnaires were used, the primary instruments for data collection. The study adopted descriptive statistics and frequency analysis. A test of hypotheses was done using regression analysis. The study found that there were positive and significant effects of compromising Strategy and integrating strategy on employee performance. The study concluded that integrating g strategy has a major effect on employee performance in Nigeria's banking industry and Nigeria banks should improve on integrating strategy because it would go a long way in enhancing employee performance and that integrity in the banks could have been achieved through strong moral principles and moral uprightness in financial transactions. It is recommended that Efforts should be made by management to organize seminars/workshops on organizational dispute resolution strategy from time to time for the employees. This will enable employees to learn about disputes and how they can be effectively managed for organizational effectiveness. Credible channels of communication and open discussions of disputes in work relations must be encouraged in an attempt to avoid confrontation, unhealthy competition, and domination as dispute resolution strategies. The study contributed to knowledge by developing a model that explains the relationship between dispute resolution and employee performance in the banking sector and also provided a framework that explains the necessity of dispute resolution and how it relates to employee performance in an organized setting.
Virulence Factors in Colorectal Cancer Metagenomes and Association of Microbial Siderophores with Advanced Stages

Colorectal cancer (CRC) is a growing public health challenge, featuring a multifactorial etiology and complex host–environment interactions. Recently, increasing evidence has pointed to the role of the gut microbiota in CRC development and progression. To explore the role of gut microbes in CRC, we retrieved metagenomic data from 156 stools from the European Nucleotide Archive database and mapped them against the VFDB database for virulence factors (VFs). GO annotations of VFs and KEGG pathways were then performed to predict the microbial functions and define functional pathways enriched in the tumor-associated microbiota. Interestingly, 306 VFs were detected in the metagenomic data. We revealed the enrichment of adenomas with VFs involved in cell adhesion, whereas in the early stages of CRC they were enriched in both adhesins and isochorismatase. Advanced stages of CRC were enriched with microbial siderophores, especially enterobactin, which was significantly associated with isochorismate synthase. We highlighted higher abundances of porins and transporters involved in antibiotic resistance and the development of biofilm in advanced stages of CRC. Most VFs detected in CRC, particularly in advanced stages, were shown to be included in siderophore biosynthesis pathways. This enrichment of predicted VFs supports the key role of the gut microbiota in the disease.
Statistical validation of simulation models of observable systems

In this paper, for validating computer simulation models of real, observable systems, an uniformly most powerful invariant (UMPI) test is developed from the generalized maximum likelihood ratio (GMLR). This test can be considered as a result of a new approach to solving the Behrens‐Fisher problem when covariance matrices of two multivariate normal populations (compared with respect to their means) are different and unknown. The test is based on invariant statistic whose distribution, under the null hypothesis, does not depend on the unknown (nuisance) parameters. The sample size and threshold of the UMPI test are determined from minimization of the weighted sum of the model builder's risk and the model user's risk. The proposed test could result in the saving of sample items, if the items of the sample are observed sequentially. In this paper, we present the exact form of the proposed curtailed procedure and examine the expected sample size savings under the null hypothesis. The sample size savings can be bounded by a constant, which is independent of the sample size. Tables are given for the expected sample size savings and maximum sample size saving under the null hypothesis for a range of significance levels (α), dimensions (p) and sample sizes (n). The curtailed test considered in this paper represents improvement over the noncurtailed or standard fixed sample tests.
A Robust Artificial Intelligence Approach with Explainability for Measurement and Verification of Energy Efficient Infrastructure for Net Zero Carbon Emissions

Rapid urbanization across the world has led to an exponential increase in demand for utilities, electricity, gas and water. The building infrastructure sector is one of the largest global consumers of electricity and thereby one of the largest emitters of greenhouse gas emissions. Reducing building energy consumption directly contributes to achieving energy sustainability, emissions reduction, and addressing the challenges of a warming planet, while also supporting the rapid urbanization of human society. Energy Conservation Measures (ECM) that are digitalized using advanced sensor technologies are a formal approach that is widely adopted to reduce the energy consumption of building infrastructure. Measurement and Verification (M&V) protocols are a repeatable and transparent methodology to evaluate and formally report on energy savings. As savings cannot be directly measured, they are determined by comparing pre-retrofit and post-retrofit usage of an ECM initiative. Given the computational nature of M&V, artificial intelligence (AI) algorithms can be leveraged to improve the accuracy, efficiency, and consistency of M&V protocols. However, AI has been limited to a singular performance metric based on default parameters in recent M&V research. In this paper, we address this gap by proposing a comprehensive AI approach for M&V protocols in energy-efficient infrastructure. The novelty of the framework lies in its use of all relevant data (pre and post-ECM) to build robust and explainable predictive AI models for energy savings estimation. The framework was implemented and evaluated in a multi-campus tertiary education institution setting, comprising 200 buildings of diverse sensor technologies and operational functions. The results of this empirical evaluation confirm the validity and contribution of the proposed framework for robust and explainable M&V for energy-efficient building infrastructure and net zero carbon emissions.
Interpretation of X-Ray Photograph of the Sun.

An x-ray picture of the sun was obtained on April 19, 1960, using pinhole-camera photography. Photometric analysis of the picture has shown that at least 75 per cent of the x radiation passed by the pinhole window material emanated from condensations in the lower corona localized above CaK plages. The x-ray plages'' appear to be of smaller dimension than the corresponding calcium plages. A strong correlation exists between the distribution of sources of x-ray emission and decimeter wave emission. When allowance is made for the transmission of the camera window material and the spectral sensitivity of the photographic film, it is estimated that the solar x-ray flux (060 A) at the earth was about 0.3 erg cm/sup -2/ sec/sup -1/ assuming a Planckian solar x-ray spectrum characterized by a temperature of 10/sup 6/ deg K. There is evidence for only a small amount of limb brightening in the non-plage background emission. The measured emission extended to about 43000 km beyond the optical limb. (auth)