Miracle-dz/UniFAR-FTUs huggingface dataset:
Mechanisms of Formation of Human Culture in Education

Abstract The relevance of the research problem lies in the necessity of an axiological approach to the formation of the personality in education and the task of strengthening the ideal image of the function. The aim of this article is studying and understanding the culture of personality formation mechanisms in relation to future specialists. The leading method of research was the theoretical analysis of philosophical and cultural approaches to the cultural formation of the personality and to the content of human culture. Content analysis was based on the philosophical and cultural concepts of V. S. Bibler, M. Buber, J. G. Herder, I. Kant, L. N. Kogan, D. S. Likhachev, A. Schweitzer, M. Scheler, and others. The experiment method was the experimental realization of formation stages of the future specialist as a person of culture, which allowed revealing the positive role of cultural mechanisms in this process. The result is the stages of human culture formation as well as mechanisms for their implementation. The article may be useful for specialists of the educational sphere, social philosophers, and culturologists.
Solubility of Some Drugs in Aqueous Solutions of Choline Chloride-Based Deep Eutectic Solvent Systems: Experimental Data, Modeling, and the Impact of Solution pH

Background The solubility of drugs in water and organic solvents is a crucial factor in numerous pharmaceutical processes. In recent years, a new type of solvent called deep eutectic solvents (DESs) has been developed as a useful solvent for drugs. Choline chloride-glycerol/urea (ChCl-G/U) systems are DESs recognized as a novel category of environmentally friendly solvents. One recent application of this type of DES in water is the solubilization of drugs. Objectives This study aimed to investigate the solubility of certain drugs in ChCl-G/U. In addition, the solubilization mechanisms of the DESs studied, and quantitative structure-property relationship (QSPR) models for solubilization were proposed. Methods The solubility of 13 drugs in an aqueous solution of the ChCl-G/U system was investigated using the shake flask method. The study was conducted at 10% and 50% mass fractions of the studied systems. Multiple linear regression models were used to develop mathematical relationships between the solubilization of the studied compounds in the presence of ChCl-G/U + water mixture using QSPR models. Results The solubility of the compounds showed a significant increase upon adding ChCl-G/U to the aqueous solutions. Based on the data obtained, QSPR models were developed using solubilization ratio and structural descriptors. Conclusions The experimental data demonstrates the potential of utilizing ChCl-G/U as a medium to enhance the solubility of poorly soluble drugs in water. Solubilization of solutes in ChCl-G/U + water mixtures could be correlated with the structural properties of drugs. Moreover, the final pH of the solutions in ChCl-U is a critical factor that must be considered when using this system for solubilization.
Two-dimensional ZnO nanosheets grown on flexible ITO-PET substrate for self-powered energy-harvesting nanodevices

Here, we report the two-step growth method of two-dimensional (2-D) ZnO nanosheets (NSs) and explore their formation mechanism. Additionally, we illustrate their application for high-performance piezoelectric nanogenerators (NGs) by using grown products from various reaction times. The result shows that NGs based on 2-D NSs demonstrated better output performance than those based on 1-D NWs, which surprisingly increased from ∼40 nA to ∼0.15 μA under the same compressive force of ∼1 kgf. It can also be observed that the output current is slightly elevated as the 2-D nanostructures become thinner. Our results offer a unique way to improve the output performance of NGs by means of controlling the synthesis period of ZnO nanostructures, which have important applications in flexible electronics and wearable devices.Here, we report the two-step growth method of two-dimensional (2-D) ZnO nanosheets (NSs) and explore their formation mechanism. Additionally, we illustrate their application for high-performance piezoelectric nanogenerators (NGs) by using grown products from various reaction times. The result shows that NGs based on 2-D NSs demonstrated better output performance than those based on 1-D NWs, which surprisingly increased from ∼40 nA to ∼0.15 μA under the same compressive force of ∼1 kgf. It can also be observed that the output current is slightly elevated as the 2-D nanostructures become thinner. Our results offer a unique way to improve the output performance of NGs by means of controlling the synthesis period of ZnO nanostructures, which have important applications in flexible electronics and wearable devices.
Multiple Point Hypothesis Test Problems and Effective Numbers of Tests for Control of the Family-Wise Error Rate

Abtsrcat We consider a specific class of multiple test problems, consisting of M simultaneous point hypothesis tests in local statistical experiments. Under certain structural assumptions the global hypothesis contains exactly one element ϑ* (say), and ϑ* is least favourable parameter configuration with respect to the family-wise error rate (FWER) of multiple single-step tests, meaning that the FWER of such tests becomes largest under ϑ*. Further-more, it turns out that concepts of positive dependence are applicable to the involved test statistics in many practically relevant cases, in particular, for multivariate normal and chi-square distributions. Altogether, this allows for a relaxation of the adjustment for multiplicity by making use of the intrinsic correlation structure in the data. We represent product-type bounds for the FWER in terms of a relaxed Šidák-type correction of the overall significance level and compute “effective numbers of tests”. Our methodology can be applied to a variety of simultaneous inference problems for multi-dimensional (location) parameters, as frequently occurring in analysis of variance models or in the context of simultaneous categorical data analysis. For example, simultaneous chi-square tests for association of categorical features are ubiquitous in genetic association studies. In this type of model, Moskvina and Schmidt (2008) gave a formula for an effective number of tests utilizing Pearson's haplotypic correlation coeffcient as a linkage disequilibrium measure. Their result follows as a corollary from our general theory and will be gen- eralized.
Real-World Data in Pharmacovigilance Database Provides a New Perspective for Understanding the Risk of Clostridium difficile Infection Associated with Antibacterial Drug Exposure

Antibacterial drug exposure (ADE) is a well-known potential risk factor for Clostridium difficile infection (CDI), but it remains controversial which certain antibacterial drugs are associated with the highest risk of CDI occurrence. To summarize CDI risk associated with ADE, we reviewed the CDI reports related to ADE in the FDA Adverse Event Reporting System database and conducted disproportionality analysis to detect adverse reaction (ADR) signals of CDI for antibacterial drugs. A total of 8063 CDI reports associated with ADE were identified, which involved 73 antibacterial drugs. Metronidazole was the drug with the greatest number of reports, followed by vancomycin, ciprofloxacin, clindamycin and amoxicillin. In disproportionality analysis, metronidazole had the highest positive ADR signal strength, followed by vancomycin, cefpodoxime, ertapenem and clindamycin. Among the 73 antibacterial drugs, 58 showed at least one positive ADR signal, and ceftriaxone was the drug with the highest total number of positive signals. Our study provided a real-world overview of CDI risk for AED from a pharmacovigilance perspective and showed risk characteristics for different antibacterial drugs by integrating its positive–negative signal distribution. Meanwhile, our study showed that the CDI risk of metronidazole and vancomycin may be underestimated, and it deserves further attention and investigation.
Simple model to simulate OCT-depth signal in weakly and strongly scattering homogeneous media

We present a simple and efficient Monte Carlo model to predict the scattering coefficients and the influence of multiple photon scattering with increasing concentration of scattering centers from optical coherence tomography (OCT) data. While the model reliably estimates optical sample parameters for a broad range of concentrations, it does not require inclusion of more complex phenomena such as dependent scattering. Instead, it relies on a particular weighting function which is introduced to describe various orders of multiple scattering events. In weakly scattering homogeneous media the measured scattering coefficient μ s depends linearly on the concentration of scattering centers. In the case of strong scattering, the dependence becomes nonlinear. Our model is able to accurately predict this nonlinearity and can be applied to extend the OCT studies of biological tissue towards determination of optical properties in the future.
Delay characterization of multilayer graphene nanoribbon interconnects in presence of scattering and thermal effects

Scattering source‐based mean free path (MFP) and circuit modeling are proposed for three different configurations of undoped multilayer graphene nanoribbon (U‐MLGNR) (viz. horizontal top‐contact (HTC), horizontal side‐contact (HSC), and vertical top‐contact (VTC)). A similar analysis is carried out for doped HTC‐MLGNR (D‐HTC‐MLGNR) considering dopants viz. Li, FeCl3, and AsF5, for a temperature range of 300–500 K. The optimistic intrinsic‐phonon limited (Λeff,1(T)) and realistic scattering limited (Λeff,2(T)) effective MFP models are considered to derive the equivalent resistance of MLGNR. The performance of MLGNR variants, considering Λeff,1(T) and Λeff,2(T), is compared to copper (Cu) (with smooth and rough surface) in terms of coupled line crosstalk‐induced delay (XT‐D). The results show that the MLGNR variants outperform Cu interconnects in terms of XT‐D, for Λeff,1(T). However, structural edge roughness being the dominant scattering source in Λeff,2(T), severely degrades the performance of MLGNR variants in comparison to Cu counterparts. Moreover, for Λeff,1(T) and Λeff,2(T), Li‐D HTC‐MLGNR outperforms other MLGNR variants. Also, among the MLGNR variants, U‐VTC‐MLGNR exhibits a minimum average relative penalty of 21.58 × 102% in terms of XT‐D, when Λeff,2(T) is considered as against Λeff,1(T). Li‐D HTC‐MLGNR with optimized width exhibits 10.59× lower XT‐D and 8.85× higher XT‐D for Λeff,1(T) and Λeff,2(T), respectively, compared to smooth Cu. The optimized Li‐D HTC‐MLGNR demonstrates a reduction of 85.48% and 74.67% in XT‐D values for Λeff,1 (T) and Λeff,2 (T), respectively, when compared to mixed carbon nanotube (MCNT) bundle interconnects.
Increasing Students’ Learning Outcomes Through the Script Model of Cooperative Learning in Secondary School

This study aims to improve student learning outcomes majoring in Social Sciences at Wawotobi High School through the application of scripted cooperative learning. This learning model is applied to determine student learning outcomes on the topic of Indonesian Natural Resources Management because students are less active during learning and are always teacher-centred, especially in student collaboration activities. The experimental research method used in this study was a one-group experimental design. This research includes pre-test and post-test. It was carried out at Wawotobi State High School in the 2021-2022 academic year. Participants were taken from the social studies major in third grade. That's about 30 students. Data collection methods include observation, tests, and documentation. The data findings conclude that t-stat t-table (-21.973 2.045), so it can be said that cooperative learning through a script model significantly increases the overall value of student learning outcomes. Learning outcomes on the subject of population dynamics in Indonesia have increased and 30 students have met the Minimum Completeness Criteria scores with a percentage of completeness learning outcomes is 100%. The results of this study recommend teachers apply a script-type cooperative learning model as alternative learning that can be done online and offline. The results of this study also have implications for teachers' understanding of the learning approach that should be used according to the needs and characteristics of students or the learning objectives to be achieved.
Numerical and Experimental Studies on Ship Motions Induced by Passing Ship

To investigate the ability of numerical models to simulate the behavior of moored ships subjected by ship-wake waves, use is made of scale model tests where a ship model sails with constant speed along a straight path at a constant distance from an otherwise motionless ship. The tests were carried out at one of the wave tanks of the Portuguese Civil Engineering Laboratory (LNEC). The moving ship is a self-propelled scale model of the “Aurora” chemical ship whereas the otherwise motionless ship is a scale model of the “Esso Osaka” tanker. The free-surface elevation was measured with a set of resistive wave gauges and ADVs. The tanker’s movements, induced by the wake waves, were measured along the six degrees of freedom with a gyroscope deployed inside the ship. The numerical model WAMIT provides, in the frequency domain, the quantities required to estimate the hydrodynamic forces associated to the interaction of a free-floating ship with waves. The BAS model uses those hydrodynamic forces to study in the time domain the ship interaction with any sea-waves acting on it. Wind and current actions can also be accounted for. The results of these numerical models are compared to the measurements made in the several repeats of one of those scale-model tests, in terms of the response amplitude to several wave components. These comparisons enabled the evaluation and validation of the numerical models parameters’ calibration process.
SELID: Selective Event Labeling for Intrusion Detection Datasets

A large volume of security events, generally collected by distributed monitoring sensors, overwhelms human analysts at security operations centers and raises an alert fatigue problem. Machine learning is expected to mitigate this problem by automatically distinguishing between true alerts, or attacks, and falsely reported ones. Machine learning models should first be trained on datasets having correct labels, but the labeling process itself requires considerable human resources. In this paper, we present a new selective sampling scheme for efficient data labeling via unsupervised clustering. The new scheme transforms the byte sequence of an event into a fixed-size vector through content-defined chunking and feature hashing. Then, a clustering algorithm is applied to the vectors, and only a few samples from each cluster are selected for manual labeling. The experimental results demonstrate that the new scheme can select only 2% of the data for labeling without degrading the F1-score of the machine learning model. Two datasets, a private dataset from a real security operations center and a public dataset from the Internet for experimental reproducibility, are used.
Development and Validation of an Operational Fast Time Ship Manoeuvring Solver to Increase Navigation Efficiency in Horizontally Restricted Waterways

: Growth of demand for containerized cargo shipping has put more ports into pressure to accommodate larger vessels. Considering the limitations on dimensions of navigation channels, this is not feasible unless aiming for significant capital dredging or alternatively creating high precision predictions of vessel motions subjected to environmental forcing and interaction with shallow and restricte d waterway. NCOS ONLINE (Nonlinear Channel Optimisation Simulator) is a state of the art navigation support tool which combines DHI’s high level forecast of environmental conditions with mathematical model of ship motions to add an extra level of accuracy in predicting the under-keel clearance and vessel swept path to boost the efficiency of navigation and pilotage within restricted channels. NCOS Manoeuvring Module utilizes an autopilot scheme based on PID (Proportional / Integral / Derivative) controller and Line of Sight Algorithm to FORCE Technology’s SimFlex4 manoeuvring solver for prediction of manoeuvring ship swept path and response, which will effectively bring the accuracy of real time full bridge simulator to fast time operation support tool. In this paper, the result of mathematical model is validated against fullscale measurements of containership transits through Port of Auckland Navigation channel by comparing pilot commands, leeway drift and swept path through output of portable p ilotage unit. According to the results the model is found promising to predict the behaviour of human pilots with precision required in operational use. Finally, the swept path and manoeuvring performance of a sample transit is assessed on different enviro nmental conditions and tide stages to evaluate the safe transit windows in operation.
TMEM106B Puncta Is Increased in Multiple Sclerosis Plaques, and Reduced Protein in Mice Results in Delayed Lipid Clearance Following CNS Injury

During inflammatory, demyelinating diseases such as multiple sclerosis (MS), inflammation and axonal damage are prevalent early in the course. Axonal damage includes swelling, defects in transport, and failure to clear damaged intracellular proteins, all of which affect recovery and compromise neuronal integrity. The clearance of damaged cell components is important to maintain normal turnover and restore homeostasis. In this study, we used mass spectrometry to identify insoluble proteins within high-speed/mercaptoethanol/sarcosyl-insoluble pellets from purified white matter plaques isolated from the brains of individuals with relapsing–remitting MS (RRMS). We determined that the transmembrane protein 106B (TMEM106B), normally lysosome-associated, is insoluble in RRMS plaques relative to normal-appearing white matter from individuals with Alzheimer’s disease and non-neurologic controls. Relative to wild-type mice, hypomorphic mice with a reduction in TMEM106B have increased axonal damage and lipid droplet accumulation in the spinal cord following myelin-oligodendrocyte-glycoprotein-induced experimental autoimmune encephalomyelitis. Additionally, the corpora callosa from cuprizone-challenged hypomorphic mice fail to clear lipid droplets efficiently during remyelination, suggesting that when TMEM106B is compromised, protein and lipid clearance by the lysosome is delayed. As TMEM106B contains putative lipid- and LC3-binding sites, further exploration of these sites is warranted.
Trends in cancer mortality among Poland’s oldest old (aged 85 years and older)

Introduction. The population of Poland’s oldest old has increased substantially in recent decades. We evaluate mortality rates for all major cancers and their trend changes between 1999–2018. Material and methods. Cancer death data (1999–2018) were extracted from the World Health Organization (WHO) database. Age-standardized rates, and annual percent changes (APC) were determined. Results. Overall, 1 out of every 8 cancers are diagnosed over age 85+. Women are more often diagnosed than men at a ratio of 2.6 to 1. With regards to the cancers with the highest mortality rates, APCs increased for lung (0.9; 95% confidence interval [CI]: 0.1–0.9) and breast (2.3; 95% CI: 1.7–2.9) cancer among women. Colon cancer also increased among men (2.7; 95% CI: 1.7–2.2). Conclusions. Substantial progress in cancer prevention has been made due to access to diagnostic testing, treatment, and a reduction of smoking. However, there is a need for comprehensive cancer centers that are equipped to administer and coordinate complex and personalized cancer care for the growing elderly population.
Biochemical and Antioxidant Profiling of Raspberry Plant Parts for Sustainable Processing

The optimization of innovation and food technological processes not only increases the profits of companies but also allows them to achieve the set goals of the green trajectory. This research aimed to collect data on the biochemical composition of different parts of the raspberry variety ‘Polka’, including the various morphological parts, to present the importance of differentiating plant parts in food processing, and to show the potential of usage for primary processing in different fields of the food industry. Fruits, stems (cane), leaves, flowers, seeds, and roots were evaluated according to their chemical composition and mineral (Ca, Mg, B, Zn, Cu, Fe, and Mn) contents, phenolic compounds, and antioxidant activity. In our study, the contents of inverted sugar, saccharose, and total sugar varied from 51.8 ± 2.46 %, 18.9 ± 0.31 %, and 69.7 ± 4,36 % in raspberry puree to 5.9 ± %, 1.51 ± %, 7.39 ± % in the seeds, respectively. The results regarding the mineral composition of various raspberry parts (mg/kg) indicated significant differences (p < 0.05). The contents of manganese and iron (57.6 ± 0.50; 36.9 ± 0.59) were the highest in all the parts in the plant. Manganese varied from 246 ± 10.32 in inflorescence to 40.1 ± 0.87 in the seeds. Iron fluctuated from 1553 ± 44.03 in the roots to 35.5 ± 0.15 in the seeds. The highest statistically significant boron content (p < 0.05) was found in the leaves (41.8 ± 0.33), while the lowest was in the seeds (7.17 ± 0.19). The total phenol content of the raspberry’s distinct parts ranged from 6500 mg GAE/100 g DW to 1700 mg GAE/100 g DW. The inflorescence had the considerably highest total phenol content. Our study found that the highest amount of epicatechin is found in the roots (9162.1 ± 647.86 mg), while the fruits contain only 657.5 ± 92.99, and the lowest value is in the stems (130.3 ± 9.22). High levels of procyanidin B2 were found in the raspberry roots (7268.7 ± 513.98), while the stems had the lowest value–368.4 ± 26.05. The DPPH of the raspberry morphological parts ranged from 145.1 to 653.6 µmol TE/g FW, ABTS—from 1091.8 to 243.4 µmol TE/g FW, and the FRAP—from 720.0 to 127.0 µmol TE/g FW. The study revealed the importance of differentiating plant parts in production for the quality of the final product. Studies showed that raspberry plant parts represent a potential source of natural food ingredients, and can be a potential raw material for products rich in phenolic compounds or dietary fiber, which can provide healthy properties to food when used as an additive that may be economically attractive for consumers.
Estimation and prediction for infinite dimensional autoregressive processes

In recent years much effort are devoted in order to predict the evolution of a discrete time stochastic processes. Few is known on the prediction of a continuous time processes on an entire time interval. For this task we introduce the p-order Banach valued autoregressive processes which appear to be a natural extension of the well-known R d -valued autoregressive processes to a functional framework. We estimate consistently the parameters of a Hilbertian autoregressive processes when are unknown and we specify the rates. In a wide range of applications this model can be used and is able to handle the prediction sucessfully.