Miracle-dz/UniFAR-FTUs huggingface dataset:
The exterior graded Swiss-Cheese Operad

ABSTRACT In this paper we introduce a generalization of the exterior algebra of a vector space V. We study some of its properties and give explicit computations for the case . In particular we show the existence and uniqueness of a determinant-like function with the property that if there exists such that . We also introduce the notion of GSC-operads and show how fits in that context.
The role of host plant usage and the accumulation of toxic secondary chemical compounds across the life cycle of a passion vine specialist butterfly

Host plant specialisation by herbivorous insects is ubiquitous, especially among the Lepidoptera. Many taxa have the ability to accumulate toxic compounds from their host plants that serve as chemical defences against natural enemies. Despite common knowledge of this pattern among insect ecologists, we still have much to learn about how dietary variation affects an insect's ability to acquire toxic plant chemicals. Longwing butterfly larvae (Heliconius) accumulate toxic cyanogenic glucosides from their host plants, passion vines (Passiflora), that make them toxic to most predators. Here, we present on zebra longwing (H. charithonia) caterpillar cohorts that were reared on native P. affinis, P. biflora, P. lutea, or P. suberosa to determine how host usage affected cyanide accumulation over larval developmental stages, and ultimately the toxicity of adult butterflies. Samples were collected at third, fourth and fifth instars, and teneral adults. Cyanogenic glucosides were extracted, the cyanide molecules were captured as sodium cyanide (CN), and CN content was quantified colorimetrically. The quantity of CN acquired increased linearly over larval ontogeny and was variable among host plants. CN concentration increased over larval development for two hosts but declined on the third. There was no clear relationship between host plant and adult CN concentrations, but adults that consumed certain hosts as larvae ended up accumulating significantly more CN, and thus expressed higher CN concentrations, than others. We demonstrated that some host plants provide specialist insects with more toxins than others and that larval secondary chemical accumulation may predict which life stages are more vulnerable to natural enemies. These conclusions support the hypothesis that host choice affects the survival of specialist insect herbivores.
Analysis of Adhesive-Bonded Cylindrical Lap Joints Subjected to Axial Load

In the currect paper, we consider the stress distribution in adhesive‐bonded cylindrical lap joints for which the two adherends, subjected to axial loads, may have arbitrary thicknesses and consist of different materials and the adhesive layer may be flexible or inflexible. Because of the difficulties in the analysis, no theoretical studies of the present problem are available in the literature. The current paper intends to seek approximate solutions by means of the principle of minimum complementary energy. All boundary stress conditions and conditions of continuity of stresses across the dividing surfaces of adhesive and adherends are strictly satisfied. Since high‐stress intensities occur in the end zones of the joint, the stress‐free end conditions of the joint need to be satisfied. By means of the present approach, closed‐form solutions are obtained. Numerical examples are provided to illustrate the effects of various parameters on the distributions and intensities of stresses in the joint.
Effect of compressibility on the Rayleigh-Taylor and Richtmyer-Meshkov instability induced nonlinear structure at two fluid interface

The effect of compressibility and of density variation on Rayleigh–Taylor and Richtmyer–Meshkov instability of the temporal development of two fluid interfacial structures such as bubbles and spikes have been investigated. It is seen that the velocity of the tip of the bubble or spike increases (destabilization) if the local Atwood number increases due to density variation of either of the fluids. The opposite is the result, i.e., the bubble or spike tip velocity decreases (stabilization) if the density variation leads to lowering of the value of the local Atwood number. The magnitude of stabilization or destabilization is an increasing function of the product of the wave number k and interfacial pressure p0. The effect of compressibility is quite varied. If the heavier (upper) fluid alone is incompressible (γh→∞), but the lighter fluid is compressible the growth rate is higher (destabilization) than when both the fluids are incompressible. Moreover the heavier fluid remaining incompressible the growth ra.
Bio-Prospecting of Crude Leaf Extracts from Thirteen Plants of Brazilian Cerrado Biome on Human Glioma Cell Lines

(1) Background: Malignant gliomas are aggressive tumors characterized by fast cellular growth and highly invasive properties. Despite all biological and clinical advances in therapy, the standard treatment remains essentially palliative. Therefore, searching for alternative therapies that minimize adverse symptoms and improve glioblastoma patients’ outcomes is imperative. Natural products represent an essential source in the discovery of such new drugs. Plants from the cerrado biome have been receiving increased attention due to the presence of secondary metabolites with significant therapeutic potential. (2) Aim: This study provides data on the cytotoxic potential of 13 leaf extracts obtained from plants of 5 families (Anacardiaceae, Annonaceae, Fabaceae, Melastomataceae e Siparunaceae) found in the Brazilian cerrado biome on a panel of 5 glioma cell lines and one normal astrocyte. (3) Methods: The effect of crude extracts on cell viability was evaluated by MTS assay. Mass spectrometry (ESI FT-ICR MS) was performed to identify the secondary metabolites classes presented in the crude extracts and partitions. (4) Results: Our results revealed the cytotoxic potential of Melastomataceae species Miconia cuspidata, Miconia albicans, and Miconia chamissois. Additionally, comparing the four partitions obtained from M. chamissois crude extract indicates that the chloroform partition had the greatest cytotoxic activity against the glioma cell lines. The partitions also showed a mean IC50 close to chemotherapy, temozolomide; nevertheless, lower toxicity against normal astrocytes. Analysis of secondary metabolites classes presented in these crude extracts and partitions indicates the presence of phenolic compounds. (5) Conclusions: These findings highlight M. chamissois chloroform partition as a promising component and may guide the search for the development of additional new anticancer therapies.
The association of motives with problematic smartphone use: A systematic review

Motives for smartphone use may be key factors underlying problematic smartphone use (PSU). However, no study has reviewed the literature investigating the association of motives with PSU. As such, we conducted a systematic review to: (a) determine which smartphone use motives were associated with PSU; and (b) examine the potential indirect and moderating effects of motives in the relationship of psychosocial factors with PSU. We identified 44 studies suitable for inclusion in our systematic review. There was extensive heterogeneity in smartphone use motives measures across the studies, including 55 different labels applied to individual motives dimensions. Categorisation of these motives based on their definitions and item content identified seven motives that were broadly assessed across the included studies. Motives which reflected smartphone use for mood regulation, enhancement, self-identity/conformity, passing time, socialising, and safety were generally positively associated with PSU. There were indirect effects of depression, anxiety, and transdiagnostic factors linked to both psychopathologies on PSU via motives, particularly those reflecting mood regulation. Stress and anxiety variously interacted with pass-time, social, and a composite of enhancement and mood regulation motives to predict PSU. However, the heterogeneity in the measurement of smartphone use motives made it difficult to determine which motives were most robustly associated with PSU. This highlights the need for a valid and comprehensive smartphone use motives measure.
Admissibility of Linear Predictors in the Superpopulation Model with Respect to Inequality Constraints under Matrix Loss Function

Admissibility of linear predictors for the linear quantity Qy is investigated in a superpopulation model with respect to some inequality constraints. Necessary and sufficient conditions for a linear predictor to be admissible in the class of homogeneous linear predictors and the class of inhomogeneous linear predictors are obtained, respectively, under matrix loss function.
Two modified conjugate gradient methods for solving unconstrained optimization and application

Conjugate gradient methods are a popular class of iterative methods for solving linear systems of equations and nonlinear optimization problems as they do not require the storage of any matrices. In order to obtain a theoretically effective and numerically efficient method, two modified conjugate gradient methods ( called the MCB1 and MCB2 methods ) are proposed. In which the coefficient βk in the two proposed methods is inspired by the structure of the conjugate gradient parameters in some existing conjugate gradient methods. Under the strong Wolfe line search, the sufficient descent property and global convergence of the MCB1 method are proved. Moreover, the MCB2 method generates a descent direction independently of any line search and produces good convergence properties when the strong Wolfe line search is employed. Preliminary numerical results show that the MCB1 and MCB2 methods are effective and robust in minimizing some unconstrained optimization problems and each of these modifications outperforms the four famous conjugate gradient methods. Furthermore, the proposed algorithms were extended to solve the problem of mode function.
Discussion on Electron Temperature of Gas-Discharge Plasma with Non-Maxwellian Electron Energy Distribution Function Based on Entropy and Statistical Physics

Electron temperature is reconsidered for weakly-ionized oxygen and nitrogen plasmas with its discharge pressure of a few hundred Pa, with its electron density of the order of 1017m−3 and in a state of non-equilibrium, based on thermodynamics and statistical physics. The relationship between entropy and electron mean energy is focused on based on the electron energy distribution function (EEDF) calculated with the integro-differential Boltzmann equation for a given reduced electric field E/N. When the Boltzmann equation is solved, chemical kinetic equations are also simultaneously solved to determine essential excited species for the oxygen plasma, while vibrationally excited populations are solved for the nitrogen plasma, since the EEDF should be self-consistently found with the densities of collision counterparts of electrons. Next, the electron mean energy U and entropy S are calculated with the self-consistent EEDF obtained, where the entropy is calculated with the Gibbs’s formula. Then, the “statistical” electron temperature Test is calculated as Test=[∂S/∂U]−1. The difference between Test and the electron kinetic temperature Tekin is discussed, which is defined as [2/(3k)] times of the mean electron energy U=〈ϵ〉, as well as the temperature given as a slope of the EEDF for each value of E/N from the viewpoint of statistical physics as well as of elementary processes in the oxygen or nitrogen plasma.
IoT & ML-Based Healthcare Monitoring System-Review

Intelligent medical management is one of several modern city and society management fields where the Internet of Things (IoT) is essential. Smart cities' current engagement between technology and the health care system is strengthened by the intelligent IoT's limitless networking capabilities for big data analysis in medicine. Allows for more practical methods for efficiently monitoring patients' health and providing medical services remotely online assessment of patients' health status by doctors, nurses, and other healthcare professionals. The abstract of the current study aims to provide a full examination of the function of IoT in medical management systems, analyse the available concerns, and address many of the open questions. It also aims to provide an up-to-date and comprehensive review of this field. Enabling technology and hints at a variety of uses There have been suggested research plans. The following are some examples of IoT applications from previous studies: wearable technology, monitoring technology, rehabilitation technology, telehealth, behaviour modification, smart city, and smart home. This comprehensive review identifies the crucial elements that make it possible to comprehend the healthcare possibilities and obstacles providers to put IoT applications into action. Lastly, anticipated COVID-19 effects on IoT uptake this review assessed in the field of healthcare.
Robust Real-Time AUV Self-Localization Based on Stereo Vision-Inertia

Autonomous underwater vehicles (AUVs) play an important role in deep-sea exploration, in which AUV self-localization is a key component. However, due to poor visibility caused by challenging marine environments, AUVs are often equipped with high-cost and heavy-weight acoustic sensors to accomplish localization tasks. We propose a robust real-time AUV self-localization method based on stereo camera and inertial sensor, which merges point and diagonal features, as well as inertial measurements to overcome the challenges of poor visibility. Our method also includes an underwater loop detection algorithm based on the combination of points and diagonal segments, which can extract effective binary descriptors in low-textured underwater scenarios. Furthermore, we develop an AUV self-localization system based on a real-time, portable, low-cost, and small volume sensor suite. Finally, we test the proposed method in a real underwater environment using our sensor suite, and the experimental results demonstrate the effectiveness of the proposed method under dramatically changing underwater scenarios.
BAYESIAN ECONOMETRICS: The First Twenty Years

This paper sketches the history of how Bayesian inference was adopted and utilized in econometrics during its first 20 years. It focuses on the causes of the Bayesian movement, the ways in which Bayesian inference was applied, the problems that the application was intended to solve, and the results achieved. It shows that Bayesian research has largely followed mainstream econometric development as far as the major econometric ideas and methods are concerned and that Bayesian reformulation of mainstream econometrics has nevertheless helped in deepening econometricians' understanding of many modeling problems by presenting them from a different angle.
Mineral Texture Classification Using Deep Convolutional Neural Networks: An Application to Zircons From Porphyry Copper Deposits

The texture and morphology of igneous zircon indicates magmatic conditions during zircon crystallization and can be used to constrain provenance. Zircons from porphyry copper deposits are typically prismatic, euhedral, and strongly oscillatory zoned which may differentiate them from zircons associated with unmineralized igneous systems. Here, cathodoluminescence images of zircons from the Quellaveco porphyry copper district, Southern Peru, were collected to compare zircon textures between the premineralization Yarabamba Batholith and the Quellaveco porphyry copper deposit. Quellaveco porphyry zircons are prismatic, euhedral, and strongly oscillatory zoned, whereas the batholith zircons are subhedral‐anhedral with weaker zoning. We adopt a deep convolutional neural network (CNN) approach to demonstrate that a CNN can classify Quellaveco porphyry zircons with high success. We trial several CNN architectures to classify zircon images: LeNet‐5, AlexNet and VGG, including a transfer learning approach where we used the weights of a VGG model pretrained on the ImageNet data set. The VGG model with transfer learning is the most effective approach, with accuracy and receiver operating characteristic‐area under curve (ROC‐AUC) scores of 0.86 and 0.93, indicating that a Quellaveco porphyry zircon CL image can be ranked higher than a batholith zircon with 93% probability. Visualizing model layer outputs demonstrates that the CNN models can recognize crystal edges, zoning, and mineral inclusions. We trial implementing trained CNN models as unsupervised feature extractors, which can empirically quantify crystal textures and morphology. Therefore, deep learning provides a tool for the extraction of information from large, imaged‐based petrographic data sets which can facilitate petrologic and provenance studies.
Portland/Sulfoaluminate Cement Blends for the Control of Early Age Hydration and Yield Stress

Early age hydration and the rheological behavior of cement pastes are related to their reactivity. The reactivity of Ordinary Portland Cement (OPC) and calcium sulfoaluminate cement (CSA) blends, with a CSA percentage of less than 10%, are investigated in this paper. Different percentages of CSA replacement are studied. First, an isothermal calorimetry study of the different cement pastes is performed to understand the effect of CSA on the evolution of the heat of hydration. Then, in order to understand the reactional mechanism of these cement pastes, X-ray diffraction (XRD) and thermogravimetric analysis (TGA/DTG) studies were conducted on one blended mix made out of 7% CSA and compared to the pure cement pastes of OPC and CSA. Later, the evolution of the yield stress as a function of the CSA percentage was studied. A synergy is shown between both OPC and CSA once mixed together, leading to a 57% and 45% higher ettringite formation for the blend compared to 100% OPC and 100% CSA cement pastes, respectively. This implies that the CSA amount affects the reactivity of OPC/CSA blends. This was confirmed by the variation in both the heat of hydration and yield stress evolution as a function of the percentage of CSA.
Tunable Couplers: An Overview of Recently Developed Couplers With Tunable Functions

With the continued development of communication technology, communication systems are required to support ever more operational frequencies and standards, which has resulted in increased complexity, cost, and size of RF front ends. Thus, miniaturized and integrated microwave devices are in high demand. In addition, frequency hopping, which helps overcome the limitations of poor anti-interference and weak security of fixed-frequency communication systems, requires the transceivers to switch to different operating frequencies and modes according to the spectrum environment. At the same time, multifunctional reconfigurable systems can free up scarce spectrum resources by switching to different operational modes depending on the spectrum environment. To leverage these advantages and to meet the aforementioned challenges and requirements of applications, it is important, both from a theoretical and an engineering standpoint, to study the integrated design of multifunctional reconfigurable microwave devices.
Time-Gated Pulsed Raman Spectroscopy with NS Laser for Cultural Heritage

Raman spectroscopy, a non-destructive reference technique, is used in heritage science to directly identify materials like pigments, minerals, or binding media. However, depending on the material, the laser source can induce a strong fluorescence signal that may mask the Raman signal during spectral detection. This photo-induced effect can prevent the detection of a Raman peak. A pulsed Raman spectroscopy, using a time-gated detection and pulsed laser, is proven capable of rejecting the fluorescence background and working with the environmental light, which makes Raman spectroscopy more adapted for in situ applications. In this paper, we investigated how an ns pulsed laser can be an excitation source of Raman spectroscopy by focusing on different parameters of laser excitation and collection. With proper implementation, this pulsed Raman technique can be used for cultural heritage with an ns pulsed laser for the first time.
Aeroelasticity at Reversed Flow Conditions — Part II: Application to Compressor Surge

The prediction of blade loads during surge is still a challenging task. In the literature, the blade loading during surge is often referred to as “surge load,” which suggests that there is a single source of blade loading. In the second part of our paper it is shown that, in reality, the “surge load” may consist of two physically different mechanisms: the pressure shock when the pressure breaks down and aeroelastic excitation (flutter) during the blow-down phase in certain cases. This leads to a new understanding of blade loading during surge. The front block of a multistage compressor is investigated. For some points of the backflow characteristic, the quasi steady-state flow conditions are calculated using a Reynolds averaged Navier-Stokes (RANS)-solver. The flow enters at the last blade row, goes backwards through the compressor and leaves the compressor in front of the inlet guide vane. The results show a very complex flow field characterized by large recirculation regions on the suction sides of the airfoils and stagnation regions close to the trailing edges of the airfoils. Based on these steady solutions, unsteady calculations are performed with a linearized aeroelasticity code. It can be shown that some of the rotor stages are aerodynamically unstable in the first torsional mode. Thus, in addition to the pressure shock, the blades may be excited by flutter during the surge blow-down phase. In spite of the short blow-down phase typical for aero-engine high pressure compressors, this may lead to very high blade stresses due to high aeroelastic excitation at these special flow conditions. The analytical results compare very well with the observations during rig testing. The correct nodal diameter of the blade vibration is reproduced and the growth rate of the blade vibration is predicted quite well, as a comparison with tip-timing measurements shows. A new flutter region in the compressor map was experimentally and analytically detected.
Unravelling an assessment puzzle: reflections on reconciling effective assessment and workload management in South African higher education

Abstract Assessment in higher education is a complex path to navigate, with unexpected twists and turns. Although many studies project the positive outcomes of assessment for learning, the outcomes do not always match the intention. Even when formative assessment is well-planned, the implementation may take such a toll, leaving a lecturer physically drained. A big puzzle with assessment in higher education is how to design formative assessment tasks that promote deep learning for students but do not increase staff workload. In this article, I explore this puzzle in relation to my teaching of a second-year module in an English course that is part of the Bachelor of Education programme at my university. I look at how the specific context of my teaching in 2021 influenced my formative assessment design and reflect critically on the affordances and constraints of the design in relation to existing conceptualisations of assessment in higher education. Lastly, I propose some possibilities for resolving the assessment puzzle and highlight the implications of these possibilities for the reconceptualisation of assessment in higher education.
Applications of diaLogic System in Individual and Team-based Problem-Solving Applications

This paper discusses the application of diaLogic, a Human-in-the-loop system, to the development of algorithmic solutions, a popular problem solving activity. diaLogic performs a bottom-up process, which tracks the dialog (speech) between team members jointly devising an algorithm to compute metrics about the cognitive activities (CAs) performed during solving. The metrics are then used to identify the nature, parameters, and order of CAs. This insight is useful to improve problem solving in teams, as described by the examples in the paper.