Miracle-dz/UniFAR-FTUs huggingface dataset:
R-squared of a Latent Interaction in Structural Equation Model: A Tutorial of Using R

Mplus (Muthén & Muthén, 1998 2017) is one popular statistical software to estimate the latent interaction effects using the latent moderated structural equation approach (LMS). However, the variance explained by a latent interaction that supports the interpretation of estimation results is not currently available from the Mplus output. To relieve human computations and to facilitate interpretations of latent interaction effects in social science research, we developed two functions (LIR & LOIR) in the R package IRmplus to calculate the R-squared of a latent interaction above and beyond the first-order simple main effects in Structural Equation Modeling. This tutorial provides a step-by-step guide for applied researchers to estimating a latent interaction effect in Mplus, and to obtaining the R-squared of a latent interaction effect using the LIR & LOIR functions. Example data and syntax are available online.
Building a path towards responsible use of Biometrics: A proposal for security and data privacy evaluation of Biometric Systems

Like many other enterprises, humanitarian organizations are investing in their digital transformation. In this sector, an important eﬀort is put into biometric solutions. The ICRC has been exploring new ways of how they could integrate biometrics into their beneﬁciary programs, as these technologies could improve the eﬃcacy of assistance as well as permit new ways of helping people across the globe. However, despite the potential advantages, the humanitarian imperative of “Do no harm” must be ensured before any new application or implementation of new technologies is integrated into humanitarian operations. As a means to ensure the individual’s privacy, dignity and safety, the ICRC needs to evaluate if biometric authentication systems could lead to any harm to individuals. In this work, we assess the diﬀerent parts of biometric authentication systems and investigate their potential risks and vulnerabilities. We further evaluate existing biometric security frameworks and extend on them by integrating the distribution of components over functional parties. With our framework we managed to construct three diﬀerent models for general biometric authentication and assessed their individual functional advantages as well as their sensitivity to external and internal attacks. Though our framework provides evaluation of general systems, we hope our research will provide the ICRC a better foothold in this rapidly expanding ﬁeld.
Learning for Life: A Workshop Report

In today's complex society we need to learn on a daily basis during our whole life, especially when it comes to new digital tools on which our lives are increasingly more dependent. However, the way digital tools are designed is not well adjusted to learning how to use these tools in the later part of life. As a result, many older adults struggle with the integration of digital tools into their daily lives. Recently, older adults started to be involved in design through sustainable participatory approaches. However, this group is very heterogeneous and characterised by varied needs that have to be addressed with a fitting approach that is currently missing in E/CSCW and participatory design. In this workshop we therefore brought together different disciplines to develop new approaches that will help us to design for sustainable tech-learning networks of older adults.
Gallium nitride surface protection during RTA annealing with a GaOxNy cap-layer

Gallium nitride (GaN) is generally considered a good candidate for power electronic devices such as Schottky barrier diodes (SBDs). Nevertheless, GaN has a strong sensitivity to high temperature treatments and a cap-layer is mandatory to protect the material surface during annealing at high temperature such as post-implantation treatments. In this work, an oxidized gallium nitride layer (GaOxNy) was generated with Oxford PECVD equipment using a N2O plasma treatment to protect the GaN surface during a rapid thermal annealing (RTA), in the range of 1000 °C–1150 °C for a few minutes. Before annealing, c-TLM patterns were processed on the GaOxNy/GaN sample to characterize its sheet resistance. After the N2O plasma treatment, the sample exhibited lower sheet resistance, indicating a better n-type conduction of the GaOxNy layer due to an excess of free carriers, compared to the as-grown GaN layer. The GaOxNy/GaN surface was then annealed at 1150 °C for 3 min and observed through AFM imaging. The surface exhibited a good quality with a low roughness, nevertheless, a low density of small hexagonal pits appeared after annealing. Finally, studies to determine an efficient etching process of the GaOxNy cap-layer were conducted using both chemical and physical approaches. We observed that efficient etching of the layer was achieved using a heated hydrofluoridric acid (HF 25%) solution. To conclude, GaOxNy has proved to be an efficient cap-layer for GaN protection at high temperature.
DOES EDUCATION REALLY IMPROVE HEALTH?

While numerous studies assess the relationship between education and health, no consensus has been reached on whether education really improves health. We perform a metaanalysis of 4866 estimates gleaned from 99 published studies that examine the health effects of education. We find that the current literature suffers from moderate publication bias towards the positive effects of education on health. After correcting for publication bias with an array of sophisticated methods, we find that the overall effect size is practically zero, indicating that education generates no discernible benefits to health. The heterogeneity analysis by Bayesian Model Averaging (BMA) and Frequentist Model Averaging (FMA) reveals that the reported estimates can be largely explained by whether the econometric models control for endogeneity of education, the types of data and the differences in health measurements. Our results also suggest that education may not be an effective policy option for promoting population health.
Content-Adaptive Model Update of Convolutional Neural Networks for Super-Resolution

Content-adaptive training and transmission of the model parameters of neural networks can boost up the SR performance with higher restoration fidelity. In this case, efficient transmission of neural network parameters are essentially needed. Thus, we propose a novel method of compressing the network model parameters based on the training of network model parameters in the sense that the residues of filter parameters and content loss are jointly minimized. So, the residues of filter parameters are only transmitted to receiver sides for different temporal portions of video under consideration. This is advantage for image restoration applications with receivers (user terminals) of low complexity. In this case, the user terminals are assumed to have a limited computation and storage resource.
Rethinking Privacy-Knowledge Modeling: About Uncovering Accepted Data Collection Business Practices as Privacy Risks

Within some new law frameworks such as General Data Protection Regulation (GDPR), and California Consumer Privacy Act (CCPA), the consent of users is required for processing their sensitive data. This situation presents a motley collection of ways to provide user’s rights over the collected data. To understand the legal implications of consent, the current Informed Consent (IC) landscape and its implications, it is necessary to understand the rationale of the business models behind generated data collections. In this paper we motivate needs on privacy-knowledge models proposed in the literature. Moreover, we intend to identify challenges that involve the mobile landscape (i.e. the nature of applications and data collection) related to privacy. This work does not intend to be a systematic review of the literature in threats to privacy models, rather to provide insights in the diverse approaches of interpreting informational privacy requirements to achieve user-centric and self-determination privacy management in system design for the ﬁeld of mobile devices. In this paper, we describe the data collection business model as a dynamic system by bringing into focus the need to rethink the current practices in this ﬁeld, which in our opinion, poses risks to data owners as well as processors.
The Importance of Goats in the World

It is a challenge to transform the mindset of subsistence farmers to consider goats as a productive asset. Goat health, breeding, housing and nutrition are the main challenges in a smallholder production system. The development of the goat market sector is informal and underdeveloped. As a result, goats have not been identified as a significant contributor to the national gross domestic product. Many development organizations consider goats a preferred livestock commodity for poverty alleviation. Therefore, it is desirable to have a systematic approach to optimize goat production for smallholders. A smallholder goat value chain works well with a focus on improved goat production, increasing business and entrepreneur skills and organizing communities for strong social capital. Heifer International has large-scale goat value chain programs for smallholders in many countries. Partnership and collaborative efforts among academic/scientific, public/private sectors, producers and civil societies are critical for sustainable smallholder goat development.
Identifying Legal Party Members from Legal Opinion Texts Using Natural Language Processing

Law and order is a ﬁeld that can highly beneﬁt from the contribution of Natural Language Processing (NLP) to its betterment. An area in which NLP can be of immense help is for information retrieval from legal documents which function as legal databases. The extraction of legal parties from the aforementioned legal documents can be iden-tiﬁed as a task of high importance since it has a signiﬁcant impact on the proceeding contemporary legal cases. This study proposes a novel deep learning methodology that can be eﬀectively used to ﬁnd a solution to the problem of identifying legal party members in legal documents. In addition to that, in this paper, we introduce a novel dataset which was created by an expert in the legal domain. Evaluations for the solu-tion presented in the paper show that our system has 90.89% precision and 91.69% recall for an unseen paragraph from a legal document, thus conforming the success of our attempt.
The modification of benzene adsorption on zigzag single-wall carbon nanotubes by carboxylation

In this work, the adsorption of benzene molecule on (10,0) functionalized zigzag single-wall carbon nanotubes was studied using density functional theory. Geometric structures, adsorption energies and electronic properties of five supercells were investigated. It was found that the carboxylation causes a notable increment in the adsorption capability of SWCNT in uptaking benzene as a pollutant molecule. The highest absorbency was achieved when benzene molecule had interaction with both SWCNT and COOH functional group through π-π interaction and hydrogen bonding.
Omnibus Law in the Job Creation Bill-Making Process: An Online Natural Language Process Analysis

This study aims to: 1) capture the discourse of omnibus law on online media, 2) analyze the differences of omnibus law discourse on online media coverage, and 3) the government’s political communication in the policy-making process. Descriptions were identified through a content analysis performed using NVivo 12 Plus to the four online medias that reported the omnibus law the most during the first 6 months of the policy making process, they are Kompas.com, Detik.com, Tempo.co, and Vivanew.com. The result indicates that there are similarities and differences in online media reporting about the omnibus law policy-making process through the Job Creation Bill. First, the similarity lies in the dominant roles and interests of the government in the policy-making process. Second, there were different issues discussed and different news sentiments by online media, such as critical, positive, and proportional sentiments. Third, to achieve its goals, the government seems to be trying to approach the legislative, which plays crucial roles in the passing process from bill to law, but not to approach workers and various groups resisting the omnibus law.
Applications of iodonium salts and iodonium ylides as precursors for nucleophilic fluorination in Positron Emission Tomography

This review summarizes the applications of iodonium compounds in the rapidly developing field of Positron Emission Tomography (PET). Reactions of diaryliodonium salts with fluoride anion have found wide practical application in PET as a fast and convenient method for the introduction of the radioactive ( 18 F)-fluoride into radiotracer molecules. The best synthetic methods for the preparation of iodonium precursors for PET are described, the mechanistic aspects of nucleophilic fluorination reaction are discussed, and specific examples of the preparation of PET radioligands are provided.
Prosodic salience in Anal Naga: where non-arbitrariness, phaticity and engagement meet

The study analyses the form and functions of two closely related non-arbitrary prosodic contours in Anal Naga (ISO 639-3:anm), a Trans-Himalayan (Tibeto-Burman) language of Northeast India. The two contours are (a) a Response-Seeking contour (RS), pronounced as a strongly accented rise-fall on the last syllable of the Intonation Unit and (b) Prosodic Intensification (PI), minimally pronounced as an identical deviant accent and maximally characterised by an abrupt shift into an extra-high pitch level (or a falsetto voice) and/or an extreme rhyme lengthening. RS has phatic, interactionmanaging functions and PI triggers content-managing interpretations. Both markers index (in the Peircean sense) the investment of the speaker’s extra-effort, thus drawing the interlocutors’ attention and triggering an interpretive (PI) or responsive (RS) action. The study analyses RS and PI as conventional/symbolic indexicals (akin to a prosodic pointing) where on the one hand the form is naturally related to the triggered meaning but on the other hand the form of the marker, its distribution and the set of its functions are language-specific conventions. The study presents a brief crosslinguistic comparison of parallel indexical-iconic prosodic contours and demonstrates how despite their non-arbitrary nature, such markers have conventionalised forms, distribution and functions. The study adds to the growing evidence for the role of nonarbitrariness in language and interaction. PAVEL OZEROV Prosodic salience in Anal Naga: where non-arbitrariness, phaticity and engagement meet CORRESPONDING AUTHOR: Pavel Ozerov University of Münster, DE pozerov@uni-muenster.de
Experimental Characterization and Modeling for Equivalence Ratio Sensing in Non-premixed Flames Using Chemiluminescence and Laser-Induced Breakdown Spectroscopy Techniques

Real-time monitoring of the local equivalence ratio is of primary importance for combustion efficiency improvement. Chemiluminescence and laser-induced breakdown spectroscopy (LIBS) measurements can be powerful tools for sensing the equivalence ratio. Radicals, such as OH*, CH*, and C2*, are formed within the flame front, and consequently, the related chemiluminescence emission can be considered as a marker to follow the evolution of combustion processes. From LIBS measurements, the ratio of two characteristic spectral lines of fuel (H) and oxidizer (O) is related to the equivalence ratio. In this work, LIBS measurements have been carried out in premixed flames of known equivalence ratio for calibration purposes. Then, the application to non-premixed flames has been performed to evaluate the local equivalence ratio. Chemiluminescence emission spectra have also been collected, and the values of OH*, CH*, and C2* have been properly evaluated, taking into account the contribution of CO2* broad band emission.
Intelligent Software Agent in E-Health System: - Review

The field of medical care is characterized by complexity, dynamism, and variety. Different challenges occur in healthcare (increasing cost of care, population growth and lack of caregivers). For that, intelligent applications with Agent Technology can provide better health care than the conventional medical system. In fact, the characteristics of Intelligent Agents (proactivity, sociability, autonomy) are a good choice to solve many problems in this regard, since the key success parameter it was the natural mapping for real-life medical issues into electronic life. The design of Multi-agent architecture will effectively paradigm the heterogeneous, distributed, and independent health treatment systems. The multi-agent systems have been used of individual healthcare processes such as a knowledge-depend medical system for complex, multi-parties depend on systems such as a total healthcare where The applied from multi-agent systems(mas) in health treatment sector also has been opened avenues for discovering innovative applications such as socialized and personalized health care models. Therefore, when creating an agent-depend simulation, one of the most important questions to consider is how to model the decision decision-making operations for the agents in the model. In the literature, the wide There are a variety of agent decision-making models available, all of them motivated by multiple goals and study questions. The research explains the advances made so far in the development of regulatory frameworks for deliberative autonomous software in a partially observable environment. In this paper, we display an overview for some of an agent that has attracted attention (Beliefs Desires and Intentions (BDI) and its derivatives such as Extensible Beliefs Desires and Intentions (EBDI), Beliefs-Desires-Obligations-Intentions (BOID)). ).
Passing from Discrete to Continuum Models of Electrostatic Energy

We analyze the passage from discrete (i.e., point) charges and the corresponding discrete electrostatic energies to a continuum charge density and the corresponding continuum electrostatic energy in the limit of a large number of point charges. Given a continuous function on a bounded region that represents a continuum charge density, we construct a sequence of point charges and prove that the corresponding discrete electrostatic energies converge to the continuum counterpart. In a more general setting, we consider a given, compactly supported, signed Radon measure in the three-dimensional space representing the distribution of charges. We construct a sequence of point charges that converge to the given signed Radon measure and show that the corresponding discrete energies converge to the continuum one defined by the signed Radon measure. Conversely, for any sequence of point charges that satisfy certain reasonable assumptions on local geometry and excluded volumes, we prove that there exists a subsequence converging to a signed Radon measure and that the corresponding discrete energies converge to the continuum one defined by the limiting signed Radon measure. Tools used in our analysis include the explicit constructions of point charges from a given signed Radon measure as well as approximation properties of signed Radon measures. Finally, we apply our discrete-to-continuum analysis to the minimization of electrostatic energy related to the classical balayage problem in the potential theory. Such minimization can be potentially applied to the modeling of charged molecular systems with heterogeneously distributed charges embedded in a continuum solvent.
An Experimental Investigation on Vegetable Oils as a Cutting Fluid under Minimum Quantity Lubrication: A Sustainable Machining Approach

Cutting fluid is a vital part of the machining process. Cutting fluid is significantly applied to lower the friction and heat generated in the machining zone. It also helps in easy chip removal, protection against oxidation, tool life improvement, and an overall improvement in the quality of the product. The current industrial practices are majorly emphasized on mineral-based oil application under flood lubrication to achieve superior quality. However, these oils and techniques are toxic and environmentally unfriendly. Machining under dry or with minimum quantity lubrication (MQL) has been mostly preferred to eliminate the use of abundant oil. The current research work has established the promising potential for vegetable oils as a cutting fluid under MQL during turning of AISI 4130 steel. The results inferred that vegetable-based cutting fluids performed better over mineral-based cutting fluids in terms of lower values of machined surface roughness, tool wear, cutting forces, and chip-tool interface temperature. The MQL machining performance in terms of cutting forces, surface roughness and tool life has been observed better in comparison to machining under flood and dry cutting conditions.
Uncertain Knowledge Graph Embedding: a Natural and Effective Approach

Uncertain Knowledge Graph (UKG) models uncertainty of the knowledge, which usually models the inherent uncertainty of relation facts in a knowledge base with a confidence value. Embedding such uncertain knowledge represents is still an unresolved challenge, although deterministic Knowledge Graph embedding has been extensively studied recently, which aims at representing entities and relations as vectors in a continuous vector space and preserving semantic information as much as possible. For capturing both structural and uncertainty information of relation facts in the continuous vector space, we propose a simple but effective two-steps approach to Uncertain Knowledge Graph Embedding (UKGE) based on the skip-gram/CBOW model and learning confidence score by Long Short-Term Memories (LSTM) neural network. We show that the embedding techniques achieve results comparing with state-of-the-art approaches on uncertain knowledge graph embedding. The approach achieves the best tradeoff between efficiency and accuracy of UKGE. Because of the simplicity, the method can also handle large size graphs in lower time consumption.
The Development of Arcs-Based Economics E-Book for Grade 11 of Senior High School

This study aimed to investigate the appropriateness of an ARCS-based economics e-book on international trade topics specifically developed for grade 11 (social study program) high school students. The focus was on the experts' assessments and students' responses to the e-book. This study adapted Borg and Gall’s learning media development model into 10 stages: (1) research and information collection, (2) planning, (3) developing preliminary e-book form product, (4) preliminary trials, (5) first revision, (6) main trial, (7) second revision, (8) operational trial, (9) third revision, and (10) dissemination of research. The researchers obtained the data using validation and questionnaire sheets and then analyzed the data descriptively. The results showed that the expert team rated the ARCS-based economics e-book’s appropriateness as very high. The media expert gave an average score of 93.75%, the content expert gave 88.09%, and the linguist gave 100%. Moreover, students also gave positive responses with an average score of 76,11%). It can be concluded that the development of an ARCS-based economic ebook for class XI SMA is appropriate for use in the learning process.