Miracle-dz/UniFAR-FTUs huggingface dataset:
The Relationship between Parenting Style and Career Planning of Vocational Students by Educational Psychology under Information Technology

It is aimed at studying the role of parenting style on the career planning of vocational students in the context of information technology. This design takes the first-year and second-year students of two higher vocational colleges as the survey objects. From the perspective of educational psychology, firstly, the parenting style scale of these students is constructed, and meanwhile, the dimension design of career planning is carried out. Secondly, through the questionnaire survey, the career planning of students and the status quo of parenting styles are investigated, and the sample data are statistically analyzed by data analysis methods such as standard deviation analysis, cluster analysis, and correlation analysis. Finally, hypotheses are formulated and justified. The results reveal that the total score for career planning and the average score of each dimension are more than 3 points, indicating that vocational students have certain plans for their future careers. There are great differences in the gender of parenting styles, and the parental acceptance/involvement (t = 3.389, p < 0.01) dimension of the parenting style of the first-year students is greatly higher than that of the second-year students. On the dimension of psychological autonomy (t = −2.066, p < 0.05), the score of second-year students is distinctly higher than that of the first year. There are obvious differences in grades from the dimensions of parental acceptance/participation and psychological autonomy. There is no observable difference in whether it is an only child (p > 0.05) and the place of origin (p > 0.05). In terms of the total score and each dimension of career planning, the authoritative type scored the highest, and the neglect type scored the lowest. Parents' participation and acceptance behavior of vocational students are markedly related to their career planning. Parental punishment and acceptance are distinctly positively correlated with the career planning of these students and their two dimensions. Psychological autonomy is memorably associated with the domain of exploration.
Current prospects on nano liquid chromatography coupled to electron ionization mass spectrometry (nanoLC-EI-MS)

Abstract NanoLC consolidates as powerful analytical technology liable to provide improved chromatographic performance and superior detection capabilities. Significant instrumental advances have been accomplished in the last 20 years to make nanoLC instruments more robust, accurate, and amenable for routine analysis. Similarly, new stationary phases and nanoLC formats provide new opportunities for separations at the miniaturized scale. Besides, nanoLC makes the hyphenation with EI-MS feasible, and a series of interfaces and interesting applications have been reported in the last years. Ei-MS offers unparallel identification capabilities, and its coupling with nanoLC has the potential to revolutionize the Performance of LC-MS untargeted studies. This manuscript makes a historical journey through the development of the nanoLC and its hyphenation with the EI-MS, exploring the more outstanding advances in that technology, discussing its scope, and identifying its limitations. We intend to give the reader a current overview of the state of the art of nanoLC and point out perspectives and future lines of advancement and improvement for new research in this area. Graphical Abstract
Nanoengineered composite materials with giant dielectric anisotropy

A nanoengineered composite material was considered in the long–wavelength regime. It consisted of a random mixture of two isotropic dielectric component materials. Each component material was composed of oriented spheroidal particles. The Bruggeman formalism was used to estimate the permittivity dyadic of the corresponding homogenized composite material (HCM). If the rotational symmetry axes of the two populations of spheroids were mutually orthogonal then the HCM was an orthorhombic biaxial material; if these two symmetry axes were mutually parallel then the HCM was a uniaxial material. The degree of anisotropy of the HCM increased as the shape of the component particles became more elongated, with the greatest degrees of anisotropy being attained when the component particles were shaped as needles or discs. Hence, nanoengineered composite materials based on simple oriented component particles may be homogenized to realize extremely large degrees of anisotropy.
Geographical Spread Of Colon And Esophagus Cancers Incidence, In Libya Using A Multivariate Spatial Model

Current researches proposed the incident patterns and the related overweight risk factor for colon and oesophagus cancers. The incidence of these cancers was mapped using many methods such as stratified by sex or in general. This research models the geographical variation in the incidence of these two related cancers to investigate the relative importance of an overweight risk factor in Libya. Data on the incidence of colon cancer and oesophagus cancer between 2015 and 2020 were obtained from the African Oncology Institute, Sabratha, Libya. These data were recorded as new observations in 22 districts yearly. The Bayesian multivariate model or Bayesian shared component model for several diseases was applied to analyse the spatial variation of incidence rates jointly. In this research. the analysis shows that the joint method gives a better relative risk estimates compared with using the BYM model and mixture model. Between 2015 to 2020, the joint incidence rates of the two cancers were relatively high (0.5-1.5) in Libya. The multiple map explained that the western and southern parts of the country were at higher risk than other parts. The component representing overweigh had medium effect of colon and esophagus cancers. This incidence risk pattern has been obtained for the men but that for women have been a little different. Using a shared component model for joint modelling of incidence rates leads to more precise estimates than models of individual disease. A common risk factor (i.e., overweight) is important and needs more attention in the allocation and delivery of public health policies.
Evaluating the Performance of Slow Sand Filters in Northern Idaho

Three slow sand filter plants in northern Idaho were studied to evaluate their ability to produce good quality water and to control Giardia cysts, to determine the effects of design and operating factors on treatment performance, and to assess the effectiveness of monitoring and sanitary surveys. During the one-year study, the plants were sampled weekly for measurement of turbidity, total and fecal coliforms, and heterotrophic plate count. Samples were also analyzed for Giardia cysts and particulates. Results showed that if a slow sand filter is designed and operated according to accepted standards, it should provide consistent and effective water treatment, including a reduction in the concentration of Giardia cysts.
Optimal Power flow Model with Storage and Renewable in IEEE 14 Bus test systems

Renewable energy sources and energy storage systems present specific challenges to the traditional optimal power flow (OPF) paradigm. First, storage devices require the OPF to model charge/discharge dynamics and the supply of generated power at a later time. Second, renewable energy sources necessitate that the OPF solution accounts for the control of conventional power generators in response to errors of renewable power forecast, which are significantly larger than the traditional load forecast errors. This paper presents a sparse formulation and solution for the affinely adjustable robust counterpart (AARC) of the multi-period OPF problem. The AARC aims at operating a storage portfolio via receding horizon control; it computes the optimal base-point conventional generation and storage schedule for the forecasted load and renewable generation, together with the constrained participation factors that dictate how conventional generation and storage will adjust to maintain feasible operation whenever the renewables deviate from their forecast. The approach is demonstrated on standard IEEE networks dispatched over a 24-h horizon with interval forecasted wind power, and the feasibility of operation under interval uncertainty is validated via Monte Carlo analysis. The computational performance of the proposed approach is compared with a conventional implementation of the AARC that employs successive constraint enforcement.
Using Google Earth Engine for the complete pipeline of temporal analysis of NDVI in Chitwan National Park of Nepal

Advent of cloud computing and Google Earth Engine has completely changed the way we acquire, manage and process large satellite data. Here, we analyze temporal dynamics of vegetation productivity in Chitwan National Park, Nepal (CNP) for the period of 1988 to 2020 using Google Earth Engine (GEE) Python API, without using local computer for data storage or analysis. Specifically, we computed normalized difference vegetation index (NDVI) from Landsat data and analyzed the time-series NDVI using a Thiel Sen estimator and by decomposing it to the trend and season components We completed remote sensing analyses including image retrieval, image analysis, classification and report generation in GEE Python API, which is a free resource. Our results showed that NDVI in CNP increased at the rate of 0.0006/year (p<0.05, R2 = 0.66). We observed variation in NDVI during pre-monsoon (p<0.05, R2 =0.79) and monsoon (p<0.05, R2 =0.79) seasons which were 0.0005/ year and 0.0007/year, respectively. An annual increase in NDVI value in CNP indicates an increase in primary productivity that is assumed to support higher animal species richness. Using NDVI in GEE Python API proved to be an effective and efficient tool for monitoring the primary productivity of ecologically important sites such as protected areas.
Asymptotic hadronic form factors in quantum chromodynamics

We present a method that makes it possible to obtain exact (in all orders in the coupling constant) asymptotic expressions for the hadronic form factors in quantum chromodynamics. The method can be used also to calculate the form factors of bound states in other field-theory models, to calculate the hadronic large-angle scattering amplitudes, and so on. By way of example, the method is used to determine the exact asymptotic form of the pion electromagnetic form factor.
Three dimensional acoustic microbubble dynamics near rigid boundary

Dynamics of cavitation microbubbles due to high intensity ultrasound are associated with important applications in biomedical ultrasound, ultrasonic cleaning and sonochemistry. Previous numerical studies on this phenomenon were for an axisymmetric configuration. In this thesis, a computational model is developed to simulate the three dimensional dynamics of acoustic bubbles by using the boundary integral method. A bubble collapses much more violently subjected to high intensity ultrasound than when under normal constant ambient pressure. A few techniques are thus implemented to address the associated numerical challenge. In particular, a high quality mesh of the bubble surface is maintained by implementing a new hybrid approach of the Lagrangian method and elastic mesh technique. It avoids the numerical instabilities which occur at a sharp jet surface as well as generates a fine mesh needed at the jet surface.
Supporting software evolution through feedback on executing/skipping energy tests for proposed source code changes

With the increasing use of battery‐powered devices comes the need to test mobile applications for energy consumption and energy issues. Unfortunately, energy testing is expensive because it is a manual, labor‐intensive process that often requires multiple, separate, energy‐measuring devices to collect energy usage data. The high costs of energy testing can negatively affect the planning process of application evolution. For example, developers might be limited in the number of changes they can include in a release because they must conservatively plan to conduct energy testing after each change.
Achieving sustainable water and land use systems in highly developed tropical landscapes

Water quality degradation from human related activities has become a pressing global issue, putting water security at risk around the world. Land use decisions can severely degrade stream water quality, compromising water supply and increasing water treatment costs. Here we examine changes in water quality over 20 years and their association with land use, urbanization, and sewage treatment in the state of São Paulo, Brazil. We also consider how a severe drought in 2014–2015 affected water quality, uncovering the potential impacts of a changing climate on water treatment costs. We analyzed water quality data between 2000 and 2019 from 230 monitoring stations focusing on seven metrics: dissolved oxygen, biological oxygen demand, total nitrogen, total phosphorus, turbidity, total dissolved solids, and fecal coliforms. We first calculated the number of times that metrics exceeded the legal thresholds and then assessed if metrics were improving or deteriorating over time. Across all stations, a large proportion of stream water samples failed to comply to the legal standards for human consumption for at least one water quality metric. This proportion was highest for total dissolved solids (30.7%) and total phosphorus (42.8%), with fewer samples exceeding the threshold for turbidity and dissolved oxygen. Deteriorating water quality trends over time were prevalent for dissolved solids (33.33%) and total nitrogen (52.45%), while dissolved oxygen exhibited the highest percentage of improving trends across watersheds (43.63%). Moreover, we observed that four of the seven metrics analyzed deteriorated during the 2014–2015 drought. Urbanization and agricultural activity led to deterioration of water quality, while improvement in sewage treatment infrastructure improved water quality across watersheds. The decline in water quality observed in the region, especially during the recent drought, highlights the need to develop land use management strategies to protect water quality and reduce growing costs of water treatment in the state.
Defect Imaging on CFRP and Honeycomb Composite Structures by Guided Waves Generated and Detected by a Sparse PZT Array

Sandwich honeycomb structures (aluminum core bonded to Carbon Fiber Reinforced Polymer (CFRP) sheets on either side) are widely employed in the aerospace industry for their high strength to mass ratio. However, they might be subjected to damages such as delaminations of the composite sheets or debondings between the face sheets and the core due to impacts or thermo-mechanical aging. In order to reduce maintaining costs and extend the service time, Guided Waves (GW) based Structural Health Monitoring (SHM) systems are considered an adequate solution. Indeed, GW propagate over long distances and exhibit low attenuation, thus allowing to monitor wide areas with a limited number of sensors. Defect imaging on CFRP composites and honeycomb composite structures using both Delay-And-Sum [1] and correlation-based algorithm Excitelet [2] is presented in this communication. A machine learning algorithm is finally implemented in order to automatically identify and isolate defects on a given cartography map. The machine learning algorithm is trained on an experimental database of false and positive results obtained on representative specimens.
Towards zero carbon buildings: issues and challenges in the New Zealand construction sector

Abstract The New Zealand Government has pledged to tackle the impacts of climate change by reducing all greenhouse gases (except biogenic methane) to zero by 2050. The construction sector, which contributes approximately 20% of New Zealand’s greenhouse gas (GHG) emissions, needs to reduce its emissions if New Zealand is to meet the net-zero carbon target by 2050. However, critical questions about the feasibility of achieving net-zero carbon targets for the entire building stock remain unanswered. We undertake an exploratory study using seventeen semi-structured interviews with New Zealand’s construction experts to examine the challenges and issues in the construction sector towards Zero Carbon Buildings (ZCBs) in New Zealand. The results illustrate significant challenges to ZCBs, including financial problems, the shortage of knowledge, capacity and capability, the insufficiency of legislation, and cultural barriers. The most crucial concern is the ability of New Zealand’s construction sector to deliver ZCBs across the value chain. The study sheds new insight into barriers to ZCBs globally by identifying comprehensive challenges related to whole-of-life building carbon reduction. We suggest the government and construction sectors must prioritise knowledge development and exchange as critical support mechanisms to enable a future towards ZCBs.
Regional Economic Growth: A Spatial Durbin Model Approach

The purpose of this study is to determine the effect of spatial dependence on Gross Regional Domestic Product (GRDP) in Central Java Province. Spatial Durbin Model (SDM) is a regression model consisting of a spatial data structure which is the development of the Spatial Autoregressive Model (SAR). There is an additional spatial effect on the component of the independent variable that is not included in the SAR model or commonly referred to as an indirect effect on the independent variable. This indicates that SDM has advantages compared to SAR because there are spatial effects on the dependent and independent variables, the spatial weighted matrix used in this study is row-normalized binary contiguity. The data used in this study is sourced from the Central Java Statistics Agency (BPS) in 2019 for 35 districts and cities, which GRDP as the dependent variable, labor, human resources, and road infrastructure as independent variables. Based on the results of the analysis, the AIC value shows that SDM is significantly better than the ordinary least square (OLS) and SAR models. SDM results show that human resources have a positive sign and a direct effect of 88.5 percent and an indirect effect of 13.1 percent. In addition, the labor variable has an indirect effect on GRDP of 22.2 percent.
Strategies and Tools to Enhance the Use of Dynamic Audiovisual Stimuli in Academic Advertising Research

Abstract Advertisers and marketers increasingly adopt and invest in audiovisual formats for their communications. In contrast, academic researchers often rely on static visual stimuli to test advertising- and marketing-related research questions. In this research note, we discuss whether and how academic research could benefit from the ability to develop and use dynamic audiovisual stimuli and we consider the validity-related trade-offs inherent in their use. We first outline the components researchers should consider in constructing dynamic audiovisual stimuli. Then, in an attempt to reduce barriers to creation of dynamic audiovisual stimuli in advertising research, we review tools researchers can use to design realistic dynamic stimuli. We conclude with ways in which the use of dynamic stimuli can open new research approaches, thus expanding advertising-related theory.
Earliest fossil record of Corylophidae from Burmese amber and phylogeny of Corylophidae (Coleoptera: Coccinelloidea)

The family Corylophidae is a moderately diverse coccinelloid beetle family. The fossil record of corylophid beetles is extremely sparse, with only one species formally described from the Eocene Baltic amber. Here we report a new corylophid genus and species, Xenostanus jiangkuni Li, Szawaryn & Cai gen. et sp. nov., from mid-Cretaceous amber from northern Myanmar (ca. 99 Ma). Xenostanus is most distinctly characterized by the antenna with 10 antennomeres and the presence of metaventral and abdominal postcoxal lines. Our phylogenetic analysis suggested Xenostanus as sister to tribe Stanini. Based on its distinctive morphology and the phylogenetic results, Xenostanus is placed in the tribe Xeno﻿stanini Li, Szawaryn & Cai trib. nov.
Emerging Bioactive Agent Delivery-Based Regenerative Therapies for Lower Genitourinary Tissues

Injury to lower genitourinary (GU) tissues, which may result in either infertility and/or organ dysfunctions, threatens the overall health of humans. Bioactive agent-based regenerative therapy is a promising therapeutic method. However, strategies for spatiotemporal delivery of bioactive agents with optimal stability, activity, and tunable delivery for effective sustained disease management are still in need and present challenges. In this review, we present the advancements of the pivotal components in delivery systems, including biomedical innovations, system fabrication methods, and loading strategies, which may improve the performance of delivery systems for better regenerative effects. We also review the most recent developments in the application of these technologies, and the potential for delivery-based regenerative therapies to treat lower GU injuries. Recent progress suggests that the use of advanced strategies have not only made it possible to develop better and more diverse functionalities, but also more precise, and smarter bioactive agent delivery systems for regenerative therapy. Their application in lower GU injury treatment has achieved certain effects in both patients with lower genitourinary injuries and/or in model animals. The continuous evolution of biomaterials and therapeutic agents, advances in three-dimensional printing, as well as emerging techniques all show a promising future for the treatment of lower GU-related disorders and dysfunctions.
AtAwAR Translate: Attention-Aware Language Translation Application in Augmented Reality for Mobile Phones

As lightweight, low-cost EEG headsets emerge, the feasibility of consumer-oriented brain–computer interfaces (BCI) increases. The combination of portable smartphones and easy-to-use EEG dry electrode headbands offers intriguing new applications and methods of human–computer interaction. In previous research, augmented reality (AR) scenarios have been identified to profit from additional user state information—such as that provided by a BCI. In this work, we implemented a system that integrates user attentional state awareness into a smartphone application for an AR written language translator. The attentional state of the user is classified in terms of internally and externally directed attention by using the Muse 2 electroencephalography headband with four frontal electrodes. The classification results are used to adapt the behavior of the translation app, which uses the smartphone’s camera to display translated text as augmented reality elements. We present the first mobile BCI system that uses a smartphone and a low-cost EEG device with few electrodes to provide attention awareness to an AR application. Our case study with 12 participants did not fully support the assumption that the BCI improves usability. However, we are able to show that the classification accuracy and ease of setup are promising paths toward mobile consumer-oriented BCI usage. For future studies, other use cases, applications, and adaptations will be tested for this setup to explore the usability.