Miracle-dz/UniFAR-FTUs huggingface dataset:
Active information-seeking in support of learning extensions of novel words

A key debate in language learning centers on how people successfully learn the extension of a novel word, despite inherent ambiguity in the input. Across two studies, we tested whether learners reduce ambiguity about a word’s extension by actively sampling the environment. Adult participants were first shown ambiguous learning situations in which novel words were presented with a set of exemplars that were drawn from a subordinate-level category (e.g., Dalmatians), a basiclevel category (e.g., dogs), or a superordinate-level category (e.g., animals). Learners then had the opportunity to sample the label of additional exemplars. Participants systematically adapted their sampling choices as a function of training. Moreover, participants varied in their sampling strategies, pursuing both confirmatory strategies (selecting exemplars similar to the training set) and constraining strategies (selecting exemplars that constrain the word’s extension). Overall, these findings show that learners spontaneously pursue sampling strategies that support generalizing novel word meanings.
D RAFT , S KETCH , AND P ROVE : G UIDING F ORMAL T HEOREM P ROVERS WITH I NFORMAL P ROOFS

The formalization of existing mathematical proofs is a notoriously difficult process. Despite decades of research on automation and proof assistants, writing formal proofs remains arduous and only accessible to a few experts. While previous studies to automate formalization focused on powerful search algorithms, no attempts were made to take advantage of available informal proofs. In this work, we introduce Draft, Sketch, and Prove (DSP), a method that maps informal proofs to formal proof sketches, and uses the sketches to guide an automated prover by directing its search to easier sub-problems. We investigate two relevant setups where informal proofs are either written by humans or generated by a language model. Our experiments and ablation studies show that large language models are able to produce wellstructured formal sketches that follow the same reasoning steps as the informal proofs. Guiding an automated prover with these sketches enhances its performance from 20.9% to 39.3% on a collection of mathematical competition problems. Figure 1: Draft, Sketch, and Prove. Starting with an informal statement, our framework yields a formal proof through a three-stage process: drafting informal proofs, mapping them into formal sketches, and proving the remaining conjectures. Concretely, an informal statement is a mathematical problem described in a mixture of natural and mathematical languages (e.g., formulae in LTEX). Then, we use a large language model to autoformalize each informal proof into a formal sketch, which is a skeleton of the formal proof with open conjectures left unproven (indicated by the <proof> blocks). The formal sketch mirrors the structure of the informal proof. Finally, the open conjectures/gaps inside each formal sketch are proved by an off-the-shelf prover. †Equal contributions as leading authors. Correspondence to: qj213@cam.ac. uk. ‡Equal contributions as senior authors.
Thermoelectric efficiency of graded SicGe1–c alloys

We consider SicGe1–c graded systems of length L = 3 mm and L = 100 nm, under the action of an electric field E, and crossed by an electrical current i, the two sides of which are kept at two different temperatures Th and Tc. The dependence on composition and temperature of the thermal conductivity is analyzed. We evaluate the thermal conductivity in correspondence of the constant temperatures T = 300 K, T = 400 K, and T = 500 K and investigate the thermoelectric efficiency of the system as a function of the stoichiometric variable c and of the effective temperature gradient T h − T c L. For each temperature, we calculate the values of c in the interval [0, 1] which realize the optimal efficiency of the thermoelectric energy conversion. The corresponding values of the thermal conductivity are determined as well. For L = 3 mm, we find that the best efficiency of thermoelectric energy conversion is achieved at T = 500 K, c = 0.325568, and λ = 7.3444 Wm−1 K−1. For L = 100 nm, we obtain the best efficiency at T = 500 K, c = 0.613937, and λ = 0.1510 Wm−1 K−1.We consider SicGe1–c graded systems of length L = 3 mm and L = 100 nm, under the action of an electric field E, and crossed by an electrical current i, the two sides of which are kept at two different temperatures Th and Tc. The dependence on composition and temperature of the thermal conductivity is analyzed. We evaluate the thermal conductivity in correspondence of the constant temperatures T = 300 K, T = 400 K, and T = 500 K and investigate the thermoelectric efficiency of the system as a function of the stoichiometric variable c and of the effective temperature gradient T h − T c L. For each temperature, we calculate the values of c in the interval [0, 1] which realize the optimal efficiency of the thermoelectric energy conversion. The corresponding values of the thermal conductivity are determined as well. For L = 3 mm, we find that the best efficiency of thermoelectric energy conversion is achieved at T = 500 K, c = 0.325568, and λ = 7.3444 Wm−1 K−1. For L = 100 nm, we obtain the best efficie.
Kronecker-Factored Second-Order Optimizers Perform First-Order Descent on Neurons

Second-order optimizers hold the potential to provide faster and more stable optimization than ﬁrst-order methods. Due to the enormous size of the curvature matrix, it is widely believed that second-order methods are computationally intractable. Therefore, several approximate algorithms have been proposed. By far the most prominent and successful ones are Kronecker-Factored, block-diagonal approximations of the curvature matrix and they are considerably more data-efﬁcient than standard ﬁrst-order methods. However, so far it had not been investigated how accurate these approximations of the curvature matrix are. Our ﬁrst contribution is to develop a tool to close this gap, namely a method to efﬁciently evaluate exact second-order updates based on a (potentially large) mini-batch estimate of the curvature matrix. We then combine this tool with a careful set of experiments to demonstrate that Kronecker-factored approximations of the curvature are rather imprecise, but nevertheless and very surprisingly offer faster optimization than exact second-order updates. Finally, to resolve this apparent contradiction, we explain how the Kronecker-factorisation induces similarity to a principled ﬁrst-order method that performs gradient descent on neuron outputs rather than individual weights. We also show that this similarity is responsible for the success of Kronecker-factored methods. All in all, our contribution offers a valuable tool to analyse second-order methods, it provides a fundamentally different and improved understanding of Kronecker-factored methods and leads to more efﬁcient optimization algorithms, both in terms of computational cost and progress per parameter update.
Experimental Investigation of Image Distortion in a Mach 6 Hypersonic Flow

OF THESIS EXPERIMENTAL INVESTIGATION OF IMAGE DISTORTION IN A MACH 6 HYPERSONIC FLOW The image distortion that is inherently present when imaging through a flow field at hypersonic speeds was investigated. The original problem involves observation of the outside world from the inside an aircraft moving at hypersonic speeds. For this work, a Mach 6 hypersonic wind tunnel at Wright Patterson Air Force Base (WPAFB) was used and optical patterns were imaged with and without flow field characteristics. Two test campaigns were scheduled to conduct experiments that would provide answers to the proposed problem of the effect on observable aberrations through flow fields. During the first test campaign, October 2017, optical patterns were laser etched on anodized aluminum inserts that would couple to a 15°-degree wedge probe that had been operated with the Mach 6 tunnel previously. During this test phase, lessons learned were extremely acknowledged for preparing for the second campaign in February-March 2019. A primary effect observed was due to tunnel vibrations that created apparent optical distortion by “smearing” the optical patterns over the acquisition time of the camera. During the second test campaign there were 2 primary test models that would be mounted in the tunnel for optical analysis. Newly manufactured steel plates were coupled to the already investigated 15°-degree wedge probe for verification of what was observed previously. Also, a 7° half angle cone was manufactured as a replica of a cone that was already in operation at WPAFB. Characterization of optical distortion was done by using a quantity known as a Strehl Ratio. The Strehl Ratio is defined as the ratio of the peak intensity of a point source from an aberrated image, which has been affected due to distortion, to the corresponding point source from a diffraction limited system. Line Distribution Functions (LDFs) were identified to expand the definition from a ratio of maximums to a ratio of the shapes of the line widths. Measured vibrational influences were extracted in both the axial and vertical directions of flow to account for any artificial distortion mechanisms. These lines in both directions created our optical patterns simultaneously giving information of vibrational influences in either direction as well as the measured distortion over the test targets. Lastly, there was an attempt to relate the experimental findings to real world applications. Considerations from the first test campaign using the wedge probe are presented for this using what is known from the General Image Quality Equation (GIQE). This was developed as an analytical solution for determining image quality parameters within the National Imagery Interpretability Rating Scale (NIIRS).
Numerical study of thermal streak spacing in turbulent boundary layer with constant heat-flux boundary condition

Direct numerical simulation (DNS) of the fully developed thermal field in a flume was performed. Constant heat flux boundary condition was imposed on the heated bottom in a way, which allowed tracing of the temperature fluctuations on the wall. Free surface boundary conditions for momentum and adiabatic boundary condition for temperature were applied on the free surface. Ill-posedness of the energy equation with such boundary conditions was removed with an additional constrain: average non-dimensional wall temperature was fixed to zero. DNS was performed at constant friction Reynolds number Re=171 and Prandtl numbers 1 and 5.4. The type of the boundary condition did not affect the profile of the mean temperature. The main difference between two types of boundary conditions is in the temperature RMS fluctuations, which retain a nonzero value on the wall for constant heat flux boundary condition, and zero for constant non-dimensional temperature. Certain changes are visible also in the behavior of skewness, flatness, and other turbulent statistics in the near-wall region. An important issue is the difference between the thermal streak spacing on the isoflux wall and the velocity streak spacing near the wall. While the thermal streaks closely follow the velocity streaks for isotemperature wall boundary condition, the temperature streaks near the isoflux wall do not coincide with the velocity low speed streaks. The DNS shows that thermal streak spacing near the wall depends on Prandtl number. Thermal streak spacing is larger than the velocity streak spacing and is approaching to the well known value of the velocity streak spacing (90-100 wall units) at Prandtl number Pr=5.4.
Control of machining cutting force Using Artificial neural networks

The constant search of industry for productivity raises and market shares, pushes the development of new products capable of giving an answer to these concerns. Specifically the machine tools makers have tried to solve these problems incrementing the capability of the machines they produce, essentially in speed and precision. The recent study of some problems associated to the machining process, has revealed the possibility of incrementing the productivity of some of vertical milling machine, only through the force control, keeping it constant and equal to the optimum value defined for the tool. The cutting force control, due to the system characteristics, can only be implemented by making use of adaptive control. In order to implement adaptive controllers we have at our disposal two technologies that have been showing good results. These technologies are Neural Networks and Fuzzy Logic. We thought that it would be of interest to research the use of Artificial Neural Networks in implementation of a controller. This has been the objective of the development of the work described in this paper. The results obtained have been encouraging, showing the possibility of Implementing those controllers in real systems.
A Novel Heterojunction CuWO 4 /g-C 3 N 4 Photocatalyst for Removal of Methylene Blue from Aqueous Solution under Visible Light Irradiation

: In this study, a series of CuWO 4 /g-C 3 N 4 composites were synthesized using a facile construction method. The structural characteristics of the composites were examined using various techniques, including XRD, SEM, SEM-EDS, FT-IR, and UV-DRS. The photocatalytic performance of the CuWO 4 /g-C 3 N 4 nanocomposites was evaluated in the degradation of methylene blue (MB) under visible light irradiation. The findings revealed that the CuWO 4 /g-C 3 N 4 composite with a mass ratio of 10% CuWO 4 displayed the highest efficiency (89%) in degrading MB during an 80-minute photodegradation process, which was consistent with the pseudo-first-order kinetics. These results clearly demonstrate that the formation of a Z-scheme CuWO 4 /g-C 3 N 4 heterojunction significantly improves the photocatalytic efficiency by promoting rapid separation of electron-hole pairs and enhancing the redox capability. Additionally, the photodegradation efficiency remained above 85% even after four cycles, suggesting the stability of the catalyst.
The effect of learning opportunity factors and efficacy belief on mathematical knowledge in the teaching process

KEYWORDS The present study investigates the influence of opportunities to learn (OTL) and mathematics teaching efficacy beliefs (MTEB) towards mathematical knowledge for teaching (MKT). Using a structured questionnaire together with paper and pencil test adapted from the literature reviewed, data were collected from 187 pre-service elementary teachers in Institute of Teacher Education Indonesia. Data were analyzed using Smart PLS 3.0. The result of the structural equation model indicated that both OTL-Practicum (β = 0.395, p < 0.001) and OTL-Program (β = 0.324, p < 0.001) were positively related to MKT. The second regression analysis was to examine the impact of mathematics teaching efficacy belief on the MKT. The results showed that mathematics teaching outcome expectancy belief (MTOEB) (β = 0.322, p < 0.001) was positively related to MKT, whereas personal mathematics teaching efficacy belief (β = 0.017, p > 0.1) was not related to MKT. Overall, the belief and OTL factors explain a total of 54% variance in MKT. Implications from these findings to the successful teacher's education program implementation in Indonesia were further elaborated.
A novel multithresholding algorithm for segmentation of the MRI images

Segmentation is a crucial stage in picture evaluation techniques. Brain magnetic resonance imaging has been accurately segmented, extensively studied because the use of these types of methods allows the detection and recognition of a wide range of disorders. Thresholding is a simple and effective method for segmenting images. But depending on how many thresholds are employed for segmentation, thresholding-based techniques tend to cost more to compute. As a result, metaheuristic algorithms are a crucial tool for multilevel thresholding that aid in determining the best values. Using a novel cuckoo search (NCS) algorithm, we have suggested a method for segmenting MRI images that is more efficient. Three different objective functions (Otsu’s method, Kapur entropy, and Tsallis entropy function) were utilised by comparing the output of the projected strategy with the Cuckoo Search (CS) algorithm.
ONLINE HEDONIC CONSUMERS’ PRIVACY AWATENESS AND PRIVACY PARADOX: A SYSTEMATIC LITERATURE REVIEW

The purpose of this paper is to provide a comprehensive review of the literature on Online Hedonic Consumers’ Privacy Paradox and Privacy Awareness. Furthermore, the authors attempt to identify a gap that can be addressed in the future by developing a comprehensive and integrated model on Online Hedonic Consumer Behaviour that focuses on their Privacy Awareness. The authors conducted a systematic literature review of the extant literature. The discussion on “Privacy”, “Privacy Paradox” and “Privacy Awareness” elucidated the differences among them, thereby helping to remove any confusions held by the researchers and readers. This review offered insight into the current status of research in this field and recognized the factor “Privacy Awareness” as a gap in the existing model on Online Hedonic Consumer Behaviour that could properly be explored in further scholarly empirical research. Managers and E-Commerce vendors could utilize the findings of this review to address their Hedonic Consumer Privacy Awareness for the growth of their online businesses. This paper lays a groundwork to explore Online Hedonic Consumer Privacy Awareness in detail. A new integrated model is suggested, which will lead to the development of a theoretical framework for researchers to further examine the mediation effect of Privacy Awareness.
THE IMPACT OF CORPORATE STRATEGY AND ORGANIZATIONAL SLACK ON CORPORATE PERFORMANCE: EVIDENCE FROM PAKISTAN

This study investigates the impact of organizational slack on the relationship between firm performance and Miles and Snow's (1978) typology. We examine a sample of 274 non-financial companies listed on the Pakistan Stock Exchange between 2006 and 2021 using panel data. In order to control auto correlation and endogeneity issues, the generalized method of moments estimation (GMM) is used to get the results. Our findings demonstrate that available or potential organizational slack strengthens the already-existing positive association between prospector, analyzer, and defender strategies and a firm's financial performance, whereas recoverable slack weakens the relationship. After taking into account endogeneity, and serial correlation, the results are robust. These findings contribute to the body of knowledge on existential dilemmas relating to the use of slack resources in the company and outline the theoretical and empirical implications of Miles and Snow's typologies.
Removal of uranium ions from aqueous solutions using nano-sized copper potassium hexacyanoferrate encapsulated O-carboxymethyl chitosan matrix by batch and fixed bed column methods

The environment is at risk from radioactive waste containing uranium ions. A nano-sized copper potassium hexacyanoferrate encapsulated O-carboxymethylchitosan (CuHCF/O-CMCs) matrix was used to extract U(VI) ions from the manufactured wastewater in this investigation. The syn- thesized CuHCF/O-CMCs nanocomposite was prepared by methylation of chitosan to form O-carboxymethylchitosan (O-CMCs). The prepared nanoparticles of copper potassium hexacy- anoferrate (CuHCF) were dispersed in the aqueous solution of O-CMCs in the presence of calcium chloride solution to give a CuHCF/O-CMCs nanocomposite. Fourier-transform infrared spectros- copy, scanning electron microscopy, energy-dispersive X-ray spectroscopy, transmission electron microscopy, X-ray diffraction, and thermal gravimetric analysis-differential scanning calorime- try confirmed the chemical structure of the synthesized CuHCF/O-CMCs composite. Effects of pH, concentration of U(VI), adsorption time, and temperature of solution on the uranium uptake using the batch method were investigated. The obtained results indicated that the highest value of removal capacity was 690 mg/g of U(VI) on the CuHCF/O-CMCs composite at pH 4, 1,000 mg/L U(VI), and 298 K. The isotherms, kinetic and thermodynamic parameters of the U(VI) adsorption were investigated. Moreover, the column method was studied for the U(VI) ions’ removal by com- posite. The kinetics and interaction behavior of the removal process in continuous columns were described using theoretical models such as the Thomas model and the Yoon–Nelson model. The Thomas model and the Yoon–Nelson model were found to fit the experimental results well. The breakthrough data gave a good fit to the Thomas model. At a flow rate of 1 mL/min and a bed height of 2 cm, U(VI) had a maximum sorption capacity of 436.03 mg/g, corresponding to 57.11% uranium ion removal. The CuHCF/O-CMCs composite was eluted using 1 M HNO 3 and can be used repetitively five times with more than 93% of initial adsorption capacity.
A Four-Arm Electrically Small Omnidirectional CP Helical Antenna and Its Expansion as a Compact and Highly Efficient Dual-CP Array

A novel ultracompact four-arm electrically small omnidirectional circularly polarized (OCP) helical antenna is reported that consists of a half-wavelength normal-mode helical antenna as the driven element and three parasitic helical arms. With the introduction of the three properly arranged parasitic arms besides the driven element, the in-phased current density is largely strengthened and thus the radiation resistance of the multiarm helical antenna is substantially enlarged from <inline-formula> <tex-math notation="LaTeX">$3.3~\Omega $ </tex-math></inline-formula> (driven-element only) to <inline-formula> <tex-math notation="LaTeX">$45~\Omega $ </tex-math></inline-formula>. Good impedance matching with standard transmission line becomes feasible. The entire volume of the design is only <inline-formula> <tex-math notation="LaTeX">$\pi $ </tex-math></inline-formula> (<inline-formula> <tex-math notation="LaTeX">$0.05\,\,\lambda _{0})^{2} \times 0.06\,\,\lambda _{0}$ </tex-math></inline-formula> (ka < 0.39). It exhibits excellent OCP radiation performance with the axial ratio (AR) and gains variations less than 0.5 and 0.3 dB in 360° in the azimuth plane. Thanks to its ultracompact size, the single element is feasible to be expanded into a compact and highly efficient collinear dual-polarized OCP (DOCP) array with higher directivity and dual-CP functionality. A four-element prototype was demonstrated. Measurement shows the array achieves the peak realized gain (RG) values of 7.55 and 7.26 dBic for RHCP and LHCP, respectively. The overlapped impedance and AR bandwidth covers 0.98–1.02 GHz with isolation greater than 25 dB between the two polarizations.