Miracle-dz/UniFAR-FTUs huggingface dataset:
Teachers’ Perceptions: the Use of Google Form as a Media to Assess Primary School Students

Google Forms is one of the educational applications that teachers in teaching activities can use to assess students. Teachers usually create questions and quizzes and process students' scores through Google Forms. This study was a qualitative study that explains the perception of elementary school teachers in using Google Forms as a medium to assess their students. The data were collected through a perception questionnaire which provided five statements and three questions about the use of Google Forms in assessment. There were 45 primary teachers as the respondents, which consisted of 37 female teachers and 8 male teachers. The data were analyzed qualitatively by presenting and explaining the data. The survey showed that most of them often use Google Forms media to assess students. The respondents agreed that Google Forms is easy to use, effective, efficient and paperless media to evaluate the students. Moreover, sometimes they also use Google Forms to conduct other activities, such as completing the administrative data of students, conducting students' attendance, and obtaining the parents' opinions. They will also continue to use Google Forms as a medium to assess their students and assist in organizing teaching and learning activities if the online learning system returns to normal (face to face). Based on the data results, Google Form can be stated as one of the applications that help teachers implement online learning to carry out online assessments for primary school students.
Can (A)I Give You a Ride? Development and Validation of the CRUISE Framework for Autonomous Vehicle Services

Advances in artificial intelligence (AI) are increasingly enabling firms to develop services that utilize autonomous vehicles (AVs). Yet, there are significant psychological barriers to adoption, and insights from extant literature are insufficient to understand customer emotions regarding AV services. To allow for a holistic exploration of customer perspectives, we synthesize multidisciplinary literature to develop the Customer Responses to Unmanned Intelligent-transport Services based on Emotions (CRUISE) framework, which lays the foundation for improved strategizing, targeting, and positioning of AV services. We subsequently provide empirical support for several propositions underpinning the CRUISE framework using representative multinational panel data (N = 27,565) and an implicit association test (N = 300). We discover four distinct customer segments based on their preferred degree of service autonomy and service risk. The segments also differ in terms of the valence and intensity of emotional responses to fully autonomous vehicle services. Additionally, exposure to positive information about AV services negatively correlates with the likelihood of membership in the two most resistant segments. Our contribution to service research is chiefly twofold; we provide: 1) a formal treatise of AV services, emphasizing their uniqueness and breadth of application, and 2) empirically validated managerial directions for effective strategizing based on the CRUISE framework.
Evaluating Blockchain Systems: A Comprehensive Study of Security and Dependability Attributes

Blockchain is the enabling technology behind decentralised, fully peer-to-peer, systems. It distributes trust across a network of autonomous entities without the need for centralised trusted authority. It is therefore easier for an attacker to add malicious nodes that remain undetected. The absence of trust results in a more vulnerable system, where adversaries may come both from the inside and outside. In this context, security guarantees become crucial to ensure blockchains’ reliability and trust. In this work, we propose a comprehensive evaluation of security attributes for blockchains. We refer to the well-established concepts of security and dependability, broadly used in distributed systems, to identify the most relevant properties for blockchains. Thus, we use such properties to evaluate five of the most prominent, platforms, such as three permissionless blockchains -Bitcoin, Ethereum 2.0, and Algorand- and two permissioned blockchains -Ethereum-private and Hyperledger Fabric. We assess security over three dimensions, i.e. the consensus, infrastructure, and smart contracts.
The combination of user experience evaluation method in asessing the application of suicide risk idea identification

The global pandemic COVID-19 has led to extreme loss of human life worldwide. The pandemic has made a profound impact on the psyche of some people, and it has led to suicide. The need for confident handling of specific risk factors for suicide is needed. Therefore, to support Indonesian governments to control the increment of suicidal ideas for adolescents using a combination of unmoderated remote usability testing (URUT) and usability metric for user experience (UMUX)-Lite. Then we adopted the school-based mental health program to make a prototype mobile application using the risk factor for suicidal ideation (RFSI) instrument to identify suicidal ideas in adolescents. Participants’ characteristics included late adolescents aged 19-22 years, male and female. The results show that the time-based efficiency on the registered task obtained from the calculation is 0.025 goals/sec. In one second, participants could complete a 0.025 of the job; although all participants could complete all tasks well and quickly, they provided good satisfaction scores. Some design improvements are needed on the prototype by considering user input.
UNI ScholarWorks UNI ScholarWorks Job Satisfaction Among Principals Job Satisfaction Among Principals

Abstract Early studies by corporate organizations related the concept of job satisfaction to work performance. Subsequently, studies in educational research began to focus on job satisfaction among teachers with little attention paid to school administrators such as principals. In the organizational hierarchy of schools, principals hold the highest position. Consequently, it is important to study the influence of job satisfaction among these administrators because of their leadership roles. This paper focuses on the sources of job satisfaction and job dissatisfaction among principals. Studies reviewed cited various sources of job satisfaction and dissatisfaction. These included the job itself, the work expectations of principals to their work outcomes, contextual difference, and job autonomy. Recommendations for the area of educational administration are included. Abstract Early studies by corporate organizations related the concept of job satisfaction to work performance. Subsequently, studies in educational research began to focus on job satisfaction among teachers with little attention paid to school administrators such as principals. In the organizational hierarchy of schools, principals hold the highest position. Consequently, it is important to study the influence of job satisfaction among these administrators because of their leadership roles. This paper focuses on the sources of job satisfaction and job dissatisfaction among principals. Studies reviewed cited various sources of job satisfaction and dissatisfaction. These included the job itself, the work expectations of principals to their work outcomes, contextual difference, and job autonomy. Recommendations for the area of educational administration are included.
Global sensitivity analysis in LCA of emerging technologies: Accounting for inputs’ variability

Life Cycle Assessment (LCA) has been widely applied over the last three decades as a standardized tool for the comprehensive environmental impact assessment of products and processes. While LCAs have traditionally been based on available data from existing processes at pilot or large scale, it is estimated that 80% of environmental impacts of a process are linked to decisions at the design phase. It is therefore worth to develop tools that allow adapting the current LCA framework for the application to early-stage schemes and emerging technologies. Several difficulties hinder LCA practitioners from conducting such studies. In particular, emerging technologies tend to differ significantly from the existing processes they aim to substitute and may have unknown future applications. They present a wider data gap linked to the lack of information on the life cycle phases. Moreover, many of these systems are still at the laboratory stage, which involves substantial differences compared to industrial scale procedures. As a result, LCAs of emerging technologies are subject to an increased level of uncertainty that needs to be estimated to contribute to the reliability and credibility of the results. Global sensitivity analysis (GSA) has been proposed by several authors as a tool to evaluate the global uncertainty of LCA results and the influence of each variable input on the total variability of the model output. However, the GSA results and their corresponding parameter ranking depend on the description of each input’s variability, namely the corresponding probability distribution used by the practitioner to model the range of values that an input may assume. In this study, we propose a protocol to evaluate the effect of the choices in the selection of inputs’ distribution functions on GSA results and provide recommendations for LCA practitioners.
to the Rebounding Gut with

Vancomycin-resistant Enterococcus faecium (VREfm) is an emerging antibiotic-resistant pathogen. Strain-level investigations are beginning to reveal the molecular mechanisms used by VREfm to colonize regions of the human bowel. However, the role of commensal bacteria during VREfm colonization, in particular following antibiotic treatment, remains largely unknown. We employed amplicon 16S rRNA gene sequencing and metabolomics in a murine model system to try and investigate functional roles of the gut microbiome during VREfm colonization. First-order taxonomic shifts between Bacteroidetes and Tenericutes within the gut microbial community composition were detected both in response to pretreatment using ceftriaxone and to subsequent VREfm challenge. Using neural networking approaches to ﬁnd cooccurrence proﬁles of bacteria and metabolites, we detected key metabolome features associated with butyric acid during and after VREfm colonization. These metabolite features were associated with Bacteroides , indicative of a transition toward a preantibiotic naive microbiome. This study shows the impacts of antibiotics on the gut ecosystem and the progression of the microbiome in response to colonization with VREfm. Our results offer insights toward identifying potential nonantibiotic alternatives to eliminate VREfm through metabolic reengineering to preferentially select for Bacteroides . interpretation—including, for example, determining the molecular formula of the chemical in the neutral charge structure, determining the theoretical monoisotopic mass, and determining the likely adduct—of MS/MS data was applied to identify unknown features. Neural networking to predict microbe-metabolite interactions. Microbiota and metabolome feature tables were analyzed using MMVEC (31) (https://github.com/biocore/mmvec) to identify microbe- metabolite interactions through their cooccurrence probabilities as predicted by neural networking. Conditional biplots were generated using Emperor . Further, microbe abundances and metabolite log centered abundance heatmaps were generated using primary derived data from multinomial regression analyses using Songbird (https://github.com/mortonjt/songbird). Data availability. Amplicon 16S rRNA gene sequencing and metabolomic data for this study were deposited in publicly available databases. Raw sequence data are available through the European Nucleotide Archive, accession number PRJEB39605. Raw spectral data for metabolomics are available through https://massive.ucsd. edu, accession number MSV000085847.
DETERMINANT OF THE AUDITOR SWITCHING ON MANUFACTURING COMPANY IN INDONESIA STOCK EXCHANGE

Research aims to test the effet of Audit Opinion (AO), Financial Distress (FD), and Corporate Growth (CG) on Auditors Switching (AS) at Manufacturing Companies. Research population is manufacturing company registered on the BEI in 2016-2020. From 192 listed companies, 43 companies were chosen as samples based on established criteria by using purposive sampling method. The data used in this research is secondary data get from the company in annual report. Method of data analysis used is logistic regression. The results showed that: AS. The conclusion research is AO able to determine company to do AS. While FD and CG have no influence to the company to do auditor switching.
Futures market approach to understanding equity premium puzzle

In this paper, another factor that aﬀects equity risk premium is derived from a simple classical monetary model, which basically adds back labor-leisure to a simple consumption-only consumption-based asset pric-ing model. If every present/future good is traded at time t = 0, just as in traditional Arrow-Debreu general equilibrium models and understanding bonds as essentially trading labor with future goods, it is inevitable that risk-free bonds have lower interest rate than ideal risk-free bonds of classical monetary models.
The Effects of Social Connections on Evacuation Decision Making during Hurricane Irma

This study investigates the inﬂuenceof individuals’social connections in their decisionto either evacuateor not evacuate in the days preceding the landfall of Hurricane Irma. Using Hurricane Irma in September 2017 as a case study, a survey was conducted on two groups (those who evacuated and those who did not evacuate) to assess people’s social connections speciﬁcally examining three dimensions: dependability, density, and diversity. These variables, together with socioeconomic variables (e.g., race/ethnicity, age, education), were considered in order to better explain the inﬂuences on evacuation decision-making. To collect accurate ephemeral decision-making data from evacuees, the surveys were completed during the evacuation for those who evacuated and shortly after the passage of Hurricane Irma for those who did not evacuate. Through statistical analyses, it was concluded that density and diversity of people’s social networks played a signiﬁcant role in the decision to evacuate or not, with evacuees having more dense and diverse relationships. On the other hand, the perceived dependability of a person’s social connections (i.e., their perceived access to re- sources and support) did not signiﬁcantly impact the decision to evacuate for Hurricane Irma. This study has important implications for adding to the knowledge base on community-based sustainable disaster pre- paredness and resilience.
The Language Divide, p-1 The language divide: The persistence of english proficiency as a gateway to the The Persistence of English Proficiency as a Gateway to the Internet: The Cases of Armenia, Azerbaijan, and Georgia

Understanding sociodemographic barriers to adoption and use of the Internet continues to be an important research topic, especially considering the increased importance of access and use of information and communication technologies around the world. Extending a digital divide framework, this study analyzes the influences on and relations among awareness, adoption, and (frequent) use of the Internet in the developing countries of Armenia, Azerbaijan, and Georgia. Data from nationally representative samples fit a model predicting that age, economic well-being, education, urbanness, and English proficiency all influence each Internet digital divide. Age, education, and urbanness are the primary determinants of awareness of the Internet. Language proficiency is the second most important determinant of adoption and the most important influence on use. Despite growing Internet adoption, inequality remains, based on sociodemographic and economic status at each Internet divide. In addition, for these linguistically isolated states, English proficiency being a strong influence on adoption and use indicates a further divide between elites and nonelites.
Estimating Water Quality Benefits

Knowledge of the benefits and costs to water users is required for a complete assessment of policies to create incentives for water-quality improving changes in agricultural production. A number of benefit estimation methods are required to handle the varying nature of water quality effects. This report reviews practical approach~s and theoretical foundations for estimating the economic value of changes in water quality to recreation, navigation, reservoirs, municipal water treatment and use, and roadside drainage ditches.
the by SSR markers

The genus Passiflora encompasses many species that are endemic to the Brazilian territory, including some with economic value. Studies on genetic diversity in this genus are fundamental because they allow understanding genetic variability and distance. The present study aimed to determine the genetic variability and distances among 10 species of the genus Passiflora by using microsatellite markers (Simple Sequence Repeat, SSR). Twenty-eight heterologous microsatellite markers were tested, but only 12 were used in the diversity analysis because they amplified in at least 80% of the species. A clear separation was observed among the subgenuses studied, as well as wide variation among the accessions of Passiflora . This knowledge enables breeders to explore diversity and transfer favorable alleles found in wild species.
Pose Estimation for Two-View Panoramas based on Keypoint Matching: a Comparative Study and Critical Analysis

Pose estimation is a crucial problem in several computer vision and robotics applications. For the two-view scenario, the typical pipeline consists of finding point correspondences between the two views and using them to estimate the pose. However, most available keypoint extraction and matching methods were designed to work with perspective images and may fail under not-affine distortions present in wide-angle or omnidirectional media, which are becoming increasingly popular in recent years. This paper presents a comprehensive comparative analysis of different keypoint matching algorithms for panoramas coupled to different linear and non-linear approaches for pose estimation. As an additional contribution, we explore a recent approach for mitigating spherical distortions using tangent plane projections, which can be coupled with any planar descriptor, and allows the adaptation of recent learning-based methods. We evaluate the combination of keypoint matching and pose estimation methods using the rotation and translation error of the estimated pose in different scenarios (indoor and outdoor), and our results indicate that SPHORB and "tangent SIFT" are competitive algorithms. We also show that tangent plane adaptations frequently present competitive results, and some optimization steps consistently improve the performance in all methods. We provide code at https://github.com/Artcs1/Keypoints
A CAUSALITY ANALYSIS OF THE MILITARY SPENDING AND ECONOMIC GROWTH: THE COLOMBIAN CASE OF 1960-2016

: This paper establish an approximation to the existing causality relation between the military expenditure and economic growth for Colombia in the period of 1960 to 2017. The methodology uses the approach of the VEC models to estimate the long-run and short-run causality between the variables and its relative impact. The results indicate causality in Granger terms only from the military expenditure to the GDP and the existence of co-integration among them. In the short-run, the impact of this variable is positive to the GDP while in the long-run the military expenditure effect negatively the growth.
ACCEPTED AUTHOR VERSION OF THE MANUSCRIPT: The chemical composition of domestic soybean seeds and the effects of partial substitution of soybean meal by raw soybean seeds in the diet on pigs’ growth performance and pork quality

The chemical composition of domestic soybean seeds and the effects of partial substitution of soybean by raw soybean seeds in the diet on pigs’ growth performance and pork quality ( m. longissimus lumborum Annals of Animal Science, DOI: Abstract The objective of the study was to determine the effect of the introduction of 5% of raw soybean seeds instead of soybean meal on the growth, feed consumption and utilization of growing pigs, also the carcass and pork quality. The growth experiment was conducted on 120 pigs of approx. 18.5 kg allocated to two dietary treatments. The animals from the control treatment (CON) were offered a diet with soybean meal, and the experimental group (EXP) was given 5% raw soybean seeds (NON-GMO, Augusta var.) instead of SBM. The experiment lasted 88 days. After the experiment, eight pigs from each group were euthanized and meat samples were collected. No diet effect on the animals’ performance and carcass quality were observed ( P >0.05). The experimental diet affected ( P <0.05) meat color, and also meat composition (higher water content and lower intramuscular fat content). The composition of fatty acids in the meat did not differ significantly, except for higher C16:1 content in the EXP group. The introduction of 5% raw soybean seeds in the diets did not impact animal performance, but it reduced some indices of the pork quality.
Robotic Complex for Harvesting Apple Crops

The article deals with the concept of building an automated system for the harvesting of apple crops. This system is a robotic complex mounted on a tractor cart, including an industrial robot and a packaging system with a container for fruit collection. The robot is equipped with a vacuum gripper and a vision system. A generator for power supply, a vacuum pump for the gripper and an equipment control system are also installed on the cart. The developed automated system will have a high degree of reliability that meets the requirements of operation in the field.
Online Appendix: Signing-out Confounding Shocks in Variance-Maximizing Identification Methods

In the simulated IRF biases in section 3, the following parameter values are used: β = 0.99, σ = 1, χ = 1, θ = 0.66, φπ = 1.5, φỹ = 0.125, ρη = 0, and ρθ = 0. ΨNR is equal to −σ 1+χ σ+χ and κ̃ is equal to (σ +χ)(1−θ)(1−βθ)/θ . The structural shocks can be mapped to the reduced form impacts that would be observed by the practitioner, and the variance-maximizing shock determined as a function of these true underlying impulses. We focus on the initial impact period in order to minimize the complexity of the algebra and assume no shock persistence. The reduced-form residuals are
landmark sequence-based indoor localization. In: 1st Workshop on Artificial Intelligence and Deep Learning for Geographic Knowledge Discovery, 7-10

This paper presents a method that uses common objects as landmarks for smartphone-based indoor localization and navigation. First, a topological map marking relative positions of common objects such as doors, stairs and toilets is generated from floor plan. Second, a computer vision technique employing the latest deep learning technology has been developed for detecting common indoor objects from videos captured by smartphone. Third, second order Hidden Markov model is applied to match detected indoor landmark sequence to topological map. We use videos captured by users holding smartphones and walking through corridors of an office building to evaluate our method. The experiment shows that computer vision technique is able to accurately and reliably detect 10 classes of common indoor objects and that second order hidden Markov model can reliably match the detected landmark sequence with the topological map. This work demonstrates that computer vision and machine learning techniques can play a very useful role in developing smartphone-based indoor positioning applications