Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessment of math anxiety as a potential tool to identify students at risk of poor acquisition of new math skills: longitudinal study of grade 9 Italian students

Introduction Numerous international educational institutions have sounded the alarm about the gradual increase in the number of students failing to achieve a sufficient level of proficiency in mathematical abilities. Thus, the growing interest in identifying possible solutions and factors interfering with learning seems justified. In recent years, special attention has accrued to the possible role played by emotional factors. Methods In the present investigation, students in the first grade of a technical vocational secondary school are followed to assess the influence of math anxiety (MA) on the development of skill acquisition in calculus. A math skills assessment test is administered on two occasions, at the beginning and end of the school year. Results Results highlighted that the score on the anxiety scale, administered at the beginning of the year, negatively correlated with the score obtained on the mathematics test, administered at the end of the school year: the higher the level of anxiety, the worse the performance. Furthermore, the score obtained in the second administration makes it possible to divide the students tested into two groups: students who improved their performance and students who did not benefit at all from repeating the test. In these two groups, an analysis of the relationships between the outcome of the end-of-year mathematics test and the level of MA at the beginning of the year showed that MA correlates negatively with performance only in students who will fail to acquire new expertise in mathematics over the course of the school year. Discussion The results suggest that MA may interfere with the smooth development of math skills. Assessing the level of MA at the beginning of the school year could prove to be a useful tool in identifying which and how many students are at risk of failing to achieve the skills expected from the usual course of instruction. A consideration of anxiety as one of the variables at play in the genesis of learning difficulties may prompt educators to modify teaching methodology and strategies by increasing focus on the impact of the emotional dimension on learning.
Theoretical-experimental method of nonlinear optics: the Z-scan technique

We did this work to help professors and students of physics and engineering in Optics and Lasers courses who require a theoretical-experimental introductory framework to nonlinear optics. We showed in this article the basic principles of the theory, focusing on third-order nonlinear optical phenomena, using the well-known Z-scan technique for its demonstration. For this, we propose the design of a simple experiment that the interested party can do in an optics laboratory. Once the data has been obtained and processed, we implemented a practical method of interpretation of the typical graphs obtained by this technique to carry out the calculations that allow the measurement of the refractive index and the nonlinear absorption coefficient in materials that present these optical properties, as the case exemplified here of nematic liquid crystals doped with an organic dye.
A Predictive Maintenance Deployment Model for IoT Scenarios

The Internet of Things (IoT) concept describes the intelligent con­nectivity of smart devices using Internet connectivity. In a continuously de­veloping IoT environment, companies try different approaches for predictive maintenance as a solution to reduce costs and the frequency of maintenance activities. Such an environment can natively foster predictive maintenance as it integrates information from different equipment to derive insights and predictions. This paper proposes a deployment model for predictive maintenance ap­proaches on industrial equipment by processing and analyzing their audio signals. Proper maintenance scheduling is necessary to prevent business costs and maintain the equipment in operational capability. The authors propose a system architecture to make predictive maintenance applicable in different industrial scenarios. The implementation exploits deep learning neural networks to detect anomalies and further classify them into categories. These machine learning techniques enable predictions of equip­ment’s conditions and thus maintenance services can be performed
Health Education Model for Elderly Hypertension on Knowledge, Attitudes, and Adherence to Following the Dietary Approaches to Stop Hypertension (DASH)

Applying the DASH diet to people with hypertension can reduce blood pressure. However, the existing phenomenon shows a low adherence to this diet. Appropriate methods of providing education are still needed as an effort to increase knowledge, attitudes, and dietary adherence. The study aimed to determine the effectiveness of educating elderly hypertensives models on knowledge, attitudes, and adherence to DASH (Dietary Approaches to Stop Hypertension) in community health centers. The study was a quasi-experimental design with one group pre-test and post-test, using purposive sampling with a sample of 40 people. The intervention had for two weeks. Collecting data using guided interviews with questionnaires that included socio-demographic characteristics, knowledge, attitudes, and adherence to the DASH diet. Statistical analysis using statistical paired sample t-test, Wilcoxon rank, and McNemar tests. The average age of the respondents was 62.62 years. Most of the women were unemployed, had hypertension < 5 years, and had a family history of hypertension. After the health education intervention, there was an increase in knowledge (p = 0.000), attitude (p = 0.000), and adherence to the DASH diet (p = 0.000) with p < 0.05. The elderly hypertensive health education model is effective in increasing the knowledge, attitudes, and adherence of elderly hypertensive patients to the DASH diet. It takes the support of families and health workers to achieve optimal DASH dietary adherence
First record of skipper genus Ochlodes scudder, 1872 (Lepidoptera: Hesperiidae) feeding on rice, with a note on the taxonomy of Ochlodes sylvanus hyrcana (Christoph, 1893) stat. rev.

We report the first record of the larvae of a species in the butterfly genus Ochlodes (Lepidoptera: Hesperiidae) feeding on rice and causing notable damage. Based on the results of DNA barcoding of the reared adults and further investigation of male and female genitalia, we revise the status of taxon hyrcana Christoph, 1893 as a subspecies of Ochlodes sylvanus (Esper, [1778]) stat. rev.
Time-resolved measurements of charge carrier dynamics in Mwir to Lwir InAs/InAsSb superlattices

All-optical time-resolved measurement techniques provide a powerful tool for investigating critical parameters that determine the performance of infrared photodetector and emitter semiconductor materials. Narrow-bandgap InAs/GaSb type-II superlattices (T2SLs) have shown great promise as next generation materials, due to superior intrinsic properties and versatility. Unfortunately, InAs/GaSb T2SLs are plagued by parasitic Shockley-Read-Hall recombination centers that shorten the carrier lifetime and limit device performance. Ultrafast pump-probe techniques and time-resolved differential-transmission measurements are used here to demonstrate that ”Ga-free” InAs/InAs1−xSbx T2SLs and InAsSb alloys do not have this same limitation and thus have significantly longer carrier lifetimes. Measurements of unintentionally doped MWIR and LWIR InAs/InAs1−xSbx T2SLs demonstrate minority carrier (MC) lifetimes of 18.4 μs and 4.5 μs at 77 K, respectively. This represents a more than two order of magnitude increase compared to the 90 ns MC lifetime measured in a comparable MWIR and LWIR InAs/GaSb T2SL. Through temperaturedependent differential-transmission measurements, the various carrier recombination processes are differentiated and the dominant recombination mechanisms identified for InAs/InAs1−xSbx T2SLs. These results demonstrate that these Ga-free materials are viable options over InAs/GaSb T2SLs and potentially bulk Hg1−xCdxTe photodetectors. In addition to carrier lifetimes, the drift and diffusion of excited charge carriers through the superlattice layers (i.e. in-plane transport) directly affects the performance of photo-detectors and emitters. All-optical ultrafast techniques were successfully used for a direct measure of in-plane diffusion coefficients in MWIR InAs/InAsSb T2SLs using a photo-generated transient grating technique at various temperatures. Ambipolar diffusion coefficients of approximately 60 cm/s were reported for MWIR InAs/InAs1−xSbx T2SLs at 293 K.
Substance Use and Mental Health Responses to COVID-19 among Rural Adolescents

Purpose: This analysis provides a cross-sectional examination of adolescent mental health and substance use, to explore whether COVID-19 related stressors had an impact on substance use. Methods: This analysis examines data from 249 adolescents (aged 12-17 years) gathered between April 2020-April 2021. Adolescents completed a one-time survey assessing COVID-19-related stressors (CDC COVID-19 question bank), anxiety (GAD-7), depression (PHQ-9)
Mathematical and numerical frameworks for metamaterials and metasurfaces

This thesis is devoted to the mathematical foundations of metasurfaces and metamaterials. It is divided into three parts. The aim of the first part is to provide a mathematical and numerical framework for the analysis and design of metasurfaces. We consider an array of plasmonic nanoparticles mounted on a perfectly conducting plate and show that at some resonant frequencies the impedance blows up, allowing for a significant reduction of the scattering from the plate. Using the spectral properties of a Neumann-Poincaré type operator, we investigate the dependency of the impedance with respect to changes in the nanoparticle geometry and configuration. In the second part, we provide a mathematical theory for understanding the mechanism behind the double-negative refractive index phenomenon in chiral materials. Herein, we rely on media that consist of only a single type of dielectric resonant element, and show how the chirality of the background medium induces double-negative refractive index metamaterial, which refracts waves negatively, hence acting as a superlens. The third part of this thesis is devoted to wave-field shaping in cavities by tunable metasurfaces. In this part, we show that one can control the wave fields created by point sources inside cavities by tailoring only the boundaries of the cavities. This is achieved through the use of a tunable reflecting metasurface, which is part of the frontiers of the cavity, and can switch its boundary conditions from Dirichlet to Neumann.
Effect of seasonal variation in dielectric properties of groundwater from Vadodara region

Abstract Groundwater samples were collected during different months from the same site from Vadodara district of Gujarat state. The complex permittivity of the water samples were precisely determined over the frequency span 20 Hz to 2 MHz. Complex permittivity spectral data were converted into complex impedance formalism. Obtained results were analysed to get information of seasonal variation in groundwater quality. Dielectric constant for all samples is found to decrease linearly and rapidly with increase in frequency up to about 4 kHz, after which it decreases slowly and achieves static value approximately 78, near 2 MHz for all water samples. Dielectric loss for the water sample collected in monsoon season (August) is the highest, which shows the presence of ions dissolved from the soil in rain water. DC resistance values, determined from the complex impedance plane plot (Z′’ vs. Z″), suggested an increase in the conductivity of the water samples collected near the end of monsoon season, due to the dissolved minerals and salts from soil. The calculated values of ε′’/ε′’ DW and ε″/ε″DW ratio for the water sample of August’18 show a relatively large increase during the post-monsoon month of August’18, above 2 kHz, as compared to other months.
Atmospheric kinetic energy spectra from global and regional NCMRWF unified modelling system

Characteristics of the atmospheric kinetic energy (KE) spectrum follow a distinct power‐law dependence in the synoptic (k−3) and mesoscales (k−5/3), where k is the horizontal wave‐number. The representation of this canonical spectral behaviour provides a testimony of the acceptability of the design, configuration and performance of a numerical weather prediction (NWP) model. Therefore, the characteristics of the KE spectrum are studied using an operational version of the high‐resolution National Centre for Medium Range Weather Forecasting (NCMRWF) Unified Model (NCUM) system considering both global (∼12 km mesh) and regional (∼4 km mesh) configurations during the northern hemispheric summer period (June–August 2020). The synoptic‐scale spectral characteristics of the NCUM global (NCUM‐G) model match well with the observed spectrum in the tropics, midlatitudes and polar regions. However, the regional NCUM model (NCUM‐R) outperforms the NCUM‐G in representing the canonical slope at mesoscales. As the NCMRWF is accelerating towards a high‐resolution 6 km global (NCUM‐G6) operational model, the spectral characteristics from NCUM‐G6 are also studied during the monsoon period. Though the representation of the mesoscale spectrum is better in NCUM‐G6 relative to NCUM‐G, the regional model surpasses both the global models while demonstrating the mesoscale characteristics close to the observed spectral slopes. Further, the mesoscale spectrum deviates gradually from the Lindborg (1999) analytical fit in the mesoscales around 20Δx (where Δx ∼ 4 km), which specifies an effective resolution of the regional model. Hence, the regional model needs refinements optimally to further reduce the energy dissipation at high wave‐numbers to improve the mesoscale features at the limits of its grid resolution.
Nonexistence of baryon number for static black holes

Wheeler has conjectured that black holes should have no well-defined baryon number, and that as a result the law of conservation of baryons should be transcended in black-hole physics. We show here that a static black hole cannot have any exterior classical scalar or massive vector fields. We consider the modifications that would arise from a quantum-theoretical treatment, and we conclude that such a black hole cannot interact with the exterior world via virtual mesons such as the π and ρ. Because of this we find no way for external measurements to assign unambiguously a baryon number to such a black hole in agreement with Wheeler's prediction.
Reduction of Microbial Content (Escherichia coli) in Well Water Using Various Processes: Microfiltration Membranes, Aeration and Bentonite Adsorption

Water is a basic need for living things. This research aims to know the reduction of microbe content (Escherichia coli) in well water by using microfiltration membrane, adsorption using bentonite and aeration. The capability of those three methods in reducing E. coli was examined on the variety of time contact: 30, 60, 90, 120,180 and 300 minutes. The result of the research shows that using those methods has shown that the optimum percentage of E. coli reduction by using microfiltration membrane with 23 Most Probable Number (MPN)/100 mL of E. coli initial concentration in well water and became 0 MPN/100 mL by 100 % of E. coli reduction. Adsorption using bentonite resulted in a 78% reduction in E. coli and reduction by using aeration, the reduction of E. coli by 21%. This study shows that microfiltration has the best ability compared to other methods.
Update on clinical research for food allergy treatment

The incidence of IgE-mediated food allergy (FA) has continued to increase over the years which places substantial burden on patient health and quality of life. With no cure for this disease, the mainstay of management has been allergen avoidance. However, there have been advancements in FA treatment in recent years with multiple clinical trials utilizing novel and innovative therapeutic strategies. A landmark event came in 2020 with the first drug approval for food allergy with the approval of a product for peanut oral immunotherapy. In addition to oral immunotherapy, different delivery systems of immunotherapy (SLIT, EPIT) are being studied in addition to probiotics, biologic agents - used as monotherapy and as an adjunct, and modified allergens has taken place with the hope to further enhance existing therapeutic options. The hope through these continued developments is for therapies to emerge that will provide a more comprehensive benefit to this patient population.
Enhanced Photocatalytic CO2 Reduction to CH4 Using Novel Ternary Photocatalyst RGO/Au-TNTAs

Photocatalytic CO2 reduction into hydrocarbon fuels is one of the most efficient processes since it serves as a renewable energy source while also lowering atmospheric CO2 levels. The development of appropriate materials and technology to attain greater yield in CO2 photoreduction is one of the key issues facing the 21st century. This study successfully fabricated novel ternary reduced graphene oxide (RGO)/Au-TiO2 nanotube arrays (TNTAs) photocatalysts to promote CO2 photoreduction to CH4. Visible light-responsive RGO/Au-TNTAs composite was synthesized by facile electrochemical deposition of Au nanoparticles (NPs) and immersion of RGO nanosheets onto TNTAs. The synthesized composite has been thoroughly investigated by FESEM, HR-TEM, XRD, XPS, FT-IR, UV-Vis DRS, and PL analyzer to explain structural and functional performance. Under the source of visible light, the maximum yield of CH4 was attained at 35.13 ppm/cm2 for the RGO/Au-TNTAs composite photocatalyst after 4 h, which was considerably higher by a wide margin than that of pure TNTAs, Au-TNTAs and RGO-TNTAs. The CO2 photoreduction of the RGO/Au-TNTAs composite has been improved due to the combined effects of Au NPs and RGO. Due to its surface plasmonic resonance (SPR) mechanism, Au NPs play a crucial role in the absorption of visible light. Additionally, the middle RGO layers serve as effective electron transporters, facilitating better separation of electron-hole pairs. The newly constructed composite would be a promising photocatalyst for future photocatalytic applications in other fields.
Using Machine Learning to Detect SMART Model Cognitive Operations in Mathematical Problem-Solving Process

Self-regulated learning (SRL) is a critical component of mathematics problem-solving. Students skilled in SRL are more likely to effectively set goals, search for information, and direct their attention and cognitive process so that they align their efforts with their objectives. An influential framework for SRL, the SMART model (Winne, 2017), proposes that five cognitive operations (i.e., searching, monitoring, assembling, rehearsing, and translating) play a key role in SRL. However, these categories encompass a wide range of behaviors, making measurement challenging – often involving observing individual students and recording their think-aloud activities or asking students to complete labor-intensive tagging activities as they work. In the current study, to achieve better scalability, we operationalized indicators of SMART operations and developed automated detectors using machine learning. We analyzed students’ textual responses and interaction data collected from a mathematical learning platform where students are asked to thoroughly explain their solutions and are scaffolded in communicating their problem-solving process. Due to the rarity in data for one of the seven SRL indicators operationalized, we built six models to reflect students’ use of four SMART operations. These models are found to be reliable and generalizable, with AUC ROCs ranging
Landing Auto‐Pilots for Aircraft Motion in Longitudinal Plane using Adaptive Control Laws Based on Neural Networks and Dynamic Inversion

This paper presents two new automatic landing systems (ALSs) for aircraft motion in longitudinal plane; the model of the landing geometry determines the flight trajectory and the aircraft calculated altitude; the flight trajectory during landing consists of two parts: the glide slope and the flare. Both designed ALSs have an adaptive system (ACS) for the aircraft output's control; for the first ALS, the output vector consists of the flying altitude and the longitudinal velocity, while, for the second ALS, the output variables are the pitch angle and the longitudinal velocity of aircraft. The second variant of ALS also contains an altitude controller providing the calculated pitch angle. The calculated altitude (for the first ALS), the calculated pitch angle (for the second ALS), and the desired flight velocity are provided to the ACS by means of a block consisting of two reference models. ACS is based on the dynamic inversion concept and contains an adaptive controller which includes a linear dynamic compensator, a state observer, a neural network, and a Pseudo Control Hedging block. The paper is focused both on the design of the two ALSs and on their complex software implementation and validation.
Algorithmic aspects of graph colourings heuristics

A proper colouring of a graph is a function that assigns a colour to each vertex with the restriction that adjacent vertices are assigned with distinct colours. Proper colourings are a natural model for many problems, like scheduling, frequency assignment and register allocation. The problem of finding a proper colouring of a graph with the minimum number of colours is a well-known NP-hard problem. In this thesis we study the Grundy number and the b-chromatic number of graphs, two parameters that evaluate some heuristics for finding proper colourings. We start by giving the state of the art of the results about these parameters. Then, we show that the problem of determining the Grundy number of bipartite or chordal graphs is NP-hard, but it is solvable in polynomial time for P5-free bipartite graphs. After, we show that the problem of determining the b-chromatic number of a chordal distance-hereditary graph is NP-hard, and we give polynomial-time algorithms for some subclasses of block graphs, complement of bipartite graphs and P4-sparse graphs. We also consider the fixed-parameter tractability of determining the Grundy number and the b-chromatic number, and in particular we show that deciding if the Grundy number (or the b-chromatic number) of a graph G is at least |V(G)| - k admits an FPT algorithm when k is the parameter. Finally, we consider the computational complexity of many problems related to comparing the b-chromatic number and the Grundy number with various other related parameters of a graph.