Miracle-dz/UniFAR-FTUs huggingface dataset:
Trust me, I am an Expert: Predicting the Credibility of Experts for Statements

Nowadays, information on any topic can be researched on the Internet. However, in addition to reputable news sources, there is also a great deal of fake news that is disseminated, e.g., via social media or in established newspapers. Thus, the veracity must be assessed for each piece of information. People, parties, and organizations want to push through their interests and sometimes do not hesitate to spread fake news. For some time now, one popular means has been to quote (supposed) experts in a field. For example, —due to his authority— Albert Einstein is often quoted by believers in God although he was primarily concerned with physics while his quotes on God are taken out of context. In this paper, we define a new task of expert suitability prediction and evaluate methods to assess the credibility of a person with reference to a statement and its context and compare it to state-of-the-art approaches applying transformer-based embeddings. In an R4 cycle in CBR this approach could be used for the ranking. In this pilot study, we restrict our experiments to researchers, which allows us to derive their expertise from their publications. Furthermore, we make a manually labeled dataset consisting of 1,700 (statement,expert) pairs where suitable experts were tediously searched out together with valuable context information (such as convincing text parts of the experts’ contexts towards a statement) publicly available to stimulate further research in this very important, but up to now underrepresented area of fake news detection.
A simple pendulum technique for the over low-velocity ranges

A method for low velocity calibration of hot-wire anemometers, in which the probe is mounted on a pendulum arm, is presented. The calibration constants are determined from recorded traces of the anemometer signal obtained in the forward swing of the pendulum with the probe mounted at two different radii along the arm. Typical calibration results are presented and the use of a modified King's law in the low Reynolds number range is discussed.
Learning a Hierarchical Latent-Variable Model of Voxelized 3D Shapes

We propose the Variational Shape Learner (VSL), a hierarchical latent-variable model for 3D shape learning. VSL employs an unsupervised, variational approach to the inference and learning of the underlying structure of voxelized 3D shapes. Our model successfully learns 3D shapes via a hierarchical latent representation, made possible through the use of skip-connections. Realistic 3D objects can be generated by sampling its latent probabilistic manifold. We show that our inference and generative model can be trained end-to-end from 2D images to perform single image 3D model retrieval. Experiments show the improved performance of our model both quantitatively and qualitatively over a range of tasks.
“Can You See What I Say?” Beyond Words: Pastoral Care Education and Practice Among the Deaf and Hard of Hearing Community

: Empathic relational communication is a key competency in spiritual care for establishing a trusting pastoral relationship. Ministry with d/Deaf persons requires a deeper level of relational skill, where attentiveness to sign language, non-manual features, visual cues and facial grammar are important for meaningful pastoral relatedness. It is widely recognized that d/Deaf persons experience higher than average healthcare access barriers and associated psychological impacts, and therefore spiritual need. In addition, d/Deaf persons develop a non-auditory approach to emotional expression and communication. The competencies of clinical pastoral education (CPE) provide a natural context to further develop the necessary deeper relational skills for healthcare ministry. This article draws on the lived experiences of a chaplain for the d/Deaf engaged in CPE and a CPE educator, in order to highlight current deficiencies in pastoral care for d/Deaf persons, and to explore and illustrate how relational empathy and spiritual connection can be deepened among d/Deaf persons in healthcare by developing the competencies of CPE.
Optics Microprismatic plane-focusing Fresnel lenses for light concentration in solar photovoltaic modules

An algorithm has been developed for modeling the parameters of microprismatic specialized plane-focusing Fresnel lenses. Such lenses are more effective for application in photovoltaic modules for concentration of sunlight compare to the traditional point-focusing Fresnel lenses. The technical parameters of photovoltaic modules with these lenses were investigated. The method for manufacturing above lenses by diamond cutting technique and subsequent thermal pressing of silicone blanks is proposed. Some samples of specialized plane-focusing microprisms, which are made using our simulation results, have been experimentally investigated.
A selection of higher-order parabolic curvature flows

This thesis is divided into two parts. In Part I we consider closed immersed surfaces in R evolving by the geometric polyharmonic heat flow. Using local energy estimates, we prove interior estimates and a positive absolute lower bound on the lifespan of solutions depending solely on the local concentration of curvature of the initial immersion in L . We further use an ε-regularity type result to prove a gap lemma for stationary solutions. Using a monotonicity argument, we then prove that a blowup of the flow approaching a singular time is asymptotic to a non-umbilic embedded stationary surface. This allows us to conclude that any solution with initial L-norm of the trace-free curvature tensor smaller than an absolute positive constant converges exponentially fast to a round sphere with radius equal to 3 √ 3V0/4π, where V0 denotes the signed enclosed volume of the initial data. In Part II we study the anisotropic polyharmonic heat flow (a flow of arbitrarily high even order) for closed curves immersed in the Minkowski plane M, which is equivalent to the Euclidean plane endowed with a closed, symmetric, convex curve called an indicatrix that endows an anisotropic distance metric on vectors in M. The indicatrix ∂U (where U ⊂ R is a convex, centrally symmetric domain) induces a second convex body, the isoperimetrix Ĩ. This set is the unique convex set that minimises the isoperimetric ratio (modulo homothetic rescaling) in the Minkowski plane. We prove that under the anisotropic polyharmonic heat flow, closed curves that are initially close to a homothetic rescaling of the isoperimetrix in an averaged L sense exists for all time and converge exponentially fast to a homothetic rescaling of the isoperimetrix that has the same enclosed area as the initial immersion.
GaN-Based T-Type Totem-Pole Rectiﬁer with ZVS Control and Reactive Power Regulation

—This paper proposes a high-efﬁciency single-phase GaN-based T-type totem-pole front-end rectiﬁer with reactive power transfer. A full-range zero voltage switching (ZVS) modulation approach for both unity power factor (PF) operation and non-unity PF operation is proposed for the GaN-based rectiﬁer in critical conduction mode (CRM) operation. T-type mode operation and switching frequency limitation are proposed to overcome the ac-line zero-crossing challenges. A digital-based control strategy is also proposed to regulate the active power and reactive power simultaneously. A 1.6 kVA prototype of the T-type totem-pole rectiﬁer is built and demonstrated with full-range ZVS operation, 98.9% full-load efﬁciency, and ﬂexible reactive power regulation.
Colouring complete multipartite and Kneser-type digraphs

The dichromatic number of a digraph $D$ is the smallest $k$ such that $D$ can be partitioned into $k$ acyclic subdigraphs, and the dichromatic number of an undirected graph is the maximum dichromatic number over all its orientations. We present bounds for the dichromatic number of Kneser graphs and Borsuk graphs, and for the list dichromatic number of certain classes of Kneser graphs and complete multipartite graphs. The bounds presented are sharp up to a constant factor. Additionally, we give a directed analogue of Sabidussi‘s theorem on the chromatic number of graph products.
Semi-Supervised Feature Learning for Off-Line Writer Identifications

Conventional approaches used supervised learning to estimate off-line writer identifications. In this study, we improved the off-line writer identifica- tions by semi-supervised feature learning pipeline, which trained the extra unla- beled data and the original labeled data simultaneously. In specific, we proposed a weighted label smoothing regularization (WLSR) method, which assigned the weighted uniform label distribution to the extra unlabeled data. We regularized the convolutional neural network (CNN) baseline, which allows learning more discriminative features to represent the properties of different writing styles. Based on experiments on ICDAR2013, CVL and IAM benchmark datasets, our results showed that semi-supervised feature learning improved the baseline meas- urement and achieved better performance compared with existing writer identifications approaches.
THE FACTOR THAT INFLUENCE TURNOVER INTENTION AMONG AVIATION MAINTENANCE PERSONNEL IN KOTA KINABALU INTERNATIONAL AIRPORT SABAH

This study aims to identify the factor that influence turnover intention among aviation maintenance personnel in Kota Kinabalu International Airport in Sabah. A total of 160 questionnaires were distributed and only a total of 104 questionnaire were analyzed for this research. Job satisfaction and organizational commitment (independent variable) influence on turnover intention (dependent variable) were tested using multiple regression. The research finding is that there is significant influence of job satisfaction and normative commitment (a component of organizational commitment) on turnover intention among aviation maintenance personnel in Kota Kinabalu International Airport. This study recommends increasing the quality of supervision and communication to increase job satisfaction. Also, to improve normative commitment this study suggests maintenance organization to recruit more local Sabahan for training to become licensed aircraft engineer and technician as this will automatically increase their commitment toward the organization as they have no thought of relocation once they start working.
Lean on Me: The Impact of Interpersonal Emotion Regulation on Mood as a Function of Binary Gender

Interpersonal Emotion Regulation (ER) refers to the use of social resources to influence the emotional response to stimuli. Given the novelty of the field and potential clinical applications, greater research is needed in this sub-field of Emotion Regulation. For this study, we investigated whether aspects of Interpersonal ER is related to an individual’s mood over a seven-day period. Furthermore, the study explored whether tendency (i.e., engagement) levels and efficacy (i.e., belief) levels would result in a change in overall emotional affect (either positive or negative). Lastly, the study added a binary gender moderating variable (i.e., men and women) to see whether there were differences in tendency and efficacy levels as a function of gender. Results demonstrated that there was no significant relationship in either positive or negative affect change with Interpersonal ER. Investigating between the binary gender groups, women reported higher levels of negative efficacy and positive tendency compared to men. Lastly, the individual groups difference showed that women have an inverse trending significance with negative tendency and positive affect.
High-Resolution Methane Mapping With the EnMAP Satellite Imaging Spectroscopy Mission

Methane (CH4) mitigation from anthropogenic sources such as in the production and transport of fossil fuels has been found as one of the most promising strategies to curb global warming in the near future. Satellite-based imaging spectrometers have demonstrated to be well-suited to detect and quantify these emissions at high spatial resolution, which allows the attribution of plumes to sources. The PRecursore IperSpettrale della Missione Applicativa (PRISMA) satellite mission (ASI, Italy) has been successfully used for this application, and the recently launched Environmental Mapping and Analysis Program (EnMAP) mission (DLR/GFZ, Potsdam, Germany) presents similar spatial and spectral characteristics (30-m spatial resolution, 30-km swath, about 8-nm spectral sampling at 2300 nm). In this work, we investigate the potential and limitations of EnMAP for CH4 remote sensing, using PRISMA as a benchmark to deduce its added value. We analyze the spectral and radiometric performance of EnMAP in the 2300-nm region used for CH4 retrievals acquired using the matched-filter method. Our results show that in arid areas, EnMAP spectral resolution is about 2.7 nm finer and the signal-to-noise ratio values are approximately twice as large, which leads to an improvement in retrieval performance. Several EnMAP examples of plumes from different sources around the world with flux rate values ranging from 1 to 20 t/h are illustrated. We show plumes from sectors such as onshore oil and gas (O&G) and coal mining, but also from more challenging sectors such as landfills and offshore O&G. We detect two plumes in a close-to-sunglint configuration dataset with unprecedented flux rates of about 1 t/h, which suggests that the detection limit in offshore areas can be considerably lower under favorable conditions.
THE ROLE OF FUND MANAGERS IN DIVERSIFYING ENDOWMENT INVESTMENT PORTFOLIOS OF MALAYSIAN PUBLIC UNIVERSITIES

Endowment is one of the most important sources of income globally for higher education institutions, and it should be invested for permanent use. Unfortunately, such funds are not optimally managed in Malaysia’s public universities. Therefore, this study was conducted to find ways to manage funds effectively among universities with the highest recorded collection of endowment funds. The participating universities in the study were: Universiti Malaya, Universiti Kebangsaan Malaysia
FAMILY BUSINESSES AND SUSTAINABLE DEVELOPMENT GOALS: WHAT IS THE INFLUENCE OF FAMILY CONTROL AND MANAGEMENT?

We analyzed the effect of family businesses participating in the Corporate Sustainability Index on adopting Sustainable Development Goals (SDGs). Our sample consisted of 43 Brazilian companies listed in the Corporate Sustainability Index (CSI) that totaled 126 observations from 2019 to 2021. We submitted the data to exploratory factor analysis to estimate the different dimensions of the SDGs (social, economic, and environmental) that, therefore, were analyzed using panel data regression. We found that family-run companies reduce practices linked to the social dimension of the SDGs. However, the fact that the company is family-owned or has family control does not influence practices linked to the SDGs in the social, economic, and environmental dimensions. We found that family-run companies are unrelated to adopting SDG practices in the economic and environmental dimensions. Our results contribute to discussions about the environment, sustainability, investments that value socio-environmental responsibility, the activities of family businesses, and adherence to the SDGs. Especially when showing that the different characteristics of family businesses in Brazil that make up the CSI generally do not imply an increase in practices related to the SDGs. Therefore, our findings can help investors, creditors, and regulatory bodies decide on adopting socio-environmental practices.
A Uniﬁed Framework to Understand Decentralized and Federated Optimization Algorithms: A Multi-Rate Feedback Control Perspective

Distributed algorithms have been playing an increasingly important role in many applications such as machine learning, signal processing, and control. In this work, we provide a fresh perspective to understand, analyze, and design distributed optimization algorithms. Through the lens of multi-rate feedback control, we show that a wide class of distributed algorithms, including popular decentralized/federated schemes, can be viewed as discretizing a certain continuous-time feedback control system, possibly with multiple sampling rates, such as decentralized gradient descent, gradient tracking, and federated averaging. This key observation not only allows us to develop a generic framework to analyze the convergence of the entire algorithm class, more importantly, it also leads to an interesting way of designing new distributed algorithms. We develop the theory behind our framework and provide examples to highlight how the framework can be used in practice.
Local Fractional Sumudu Variational Iteration Method for Solving Partial Differential Equations with Local Fractional Derivative

In this paper, we combine the Sumudu transform method with the Adomian decomposition method in the sense of local fractional derivative, for solving linear and nonlinear local fractional partial differential equations. This method is called the Local Fractional Sumudu Variational Iteration Method (LFSVIM). The LFSVIM can easily be applied to many problems and is capable of reducing the size of computational work to find non-differentiable solutions to local fractional partial differential equations. Some illustrative examples are given, revealing the effectiveness and convenience of the method.
ERD¨OS DISTANCE PROBLEMS

Consider n points in the plane. In 1946, Paul Erd¨os proposed two questions relating to distances between pairs of points. What is the maximum amount of pairs that are exactly one unit distance apart? What is the minimum amount of distinct distances between pairs of points. We will discuss the current best known bounds on these questions.
Mind the Pool: Convolutional Neural Networks Can Overfit Input Size

We demonstrate how convolutional neural networks can overfit the input size: The accuracy drops significantly when using certain sizes, compared with favorable ones. This issue is inherent to pooling arithmetic, with standard downsampling layers playing a major role in favoring certain input sizes and skewing the weights accordingly. We present a solution to this problem by depriving these layers from the arithmetic cues they use to overfit the input size. Through various examples, we show how our proposed spatially-balanced pooling improves the generalization of the network to arbitrary input sizes and its robustness to translational shifts
Reflective practice to bridge the theory-gap practice in Human-Computer interaction classes

There is a need to incorporate reflective practice in students’ studies at higher education institutions to bridge the perceived theory-practice gap in Human-Computer Interaction classes. Reflective practice as an approach is employed for students to make connections between theory and practice. Reflective practice allows students to evaluate what they have learned through practice. The action research methodology was used to facilitate the research. All students who completed the assignment were invited to participate in the study, and since it was voluntary, 24 students took part. Using reflective sheets, the students were able to evaluate their current actions to improve in the future. Data were analyzed using conventional content analysis to interpret the data. The results indicated that the students were able to reflect on their work and new ideas they can incorporate into their future work. The relevance of reflective practice to bridge the theory-practice gap is highlighted.
Descriptors in fruits of avocado in Mexico

Persea schiedeana Nees is a fruit tree native to Mesoamerica, partially endemic to Mexico, found along the plain of the Gulf of Mexico. The objective was to evaluate the edaphoclimatic, morphological and chemical descriptors and compare the differences between the study regions that allow their revaluation. The study regions were: Soconusco in Tuxtla Chico, Chiapas, Selva in Palenque, Chiapas; Chontalpa in Comalcalco, Tabasco and Sierra Nororiental in Teziutlán, Puebla. In July 2019, 5 trees were randomly selected from each region for the harvest of 44 fruits, giving a total of 176 fruits and 1 584 determinations. An analysis of variance was performed to find the differences between regions and a Tukey test for the comparison of means of the morphological and physicochemical parameters evaluated, using the statistical software Minitab ® . The fruits from the Selva region in Palenque, Chiapas, presented greater value in weight (417.5 ±69.7 g), length (18.48 ±1.56 cm), pulp (282.09 ±54.72%) and fat (50.29 ±2.03%). The Soconusco region, Chiapas reached the highest percentages of protein in pulp (2.79 ±0.54%), seed (1.76 ±0.14%) and peel (2.64 ±0.19%). The results obtained suggest the existence of variation between the materials of Persea schiedeana Nees in the regions studied, allowing the identification of those with agroindustrial potential, constituting an alternative to diversify the production of Persea spp. , in Mexico.
Lecture Notes on Software Fault Isolation

In the previous lecture we added memory to our language. We assume that the memory is just an array of values indexed by integers in the range [0, U ], and that it is undefined on any indices outside this range. Programs can read from memory by dereferencing it with the syntax Mem(e), and update it with the syntax Mem(e) := ẽ. We introduced axioms for reasoning about memory updates, being careful about bounds on accesses as necessary.
Mind the Gap: Factors Which Inhibit Supporting Student Teachers to Engage in Action Research While on School Placement

In the Irish context, there is an expectation for research to be embedded across the continuum of the teaching profession, including initial teacher education. The Teaching Council has set out the requirement for student teachers to engage in research on their own practice, while on school placement, which links learning in their higher education institutions and the host school. This paper aims to examine some of the factors which inhibit support for student teachers to engage in action research while on school placement. This case study uses a constructivist and interpretivist philosophy. The design and analysis are underpinned by the triangulation of qualitative data collection through questionnaires, focus groups, group interviews and semi-structured interviews. Themes are developed using thematic analysis. Key findings include challenges encountered in supporting student teachers to engage in action research, not least conducting research ethically, and the power dynamics at play in school placement.