Miracle-dz/UniFAR-FTUs huggingface dataset:
Cutting force analysis of oak for the development of a cutting force model

ABSTRACT The cutting process of oak (Quercus robur) was investigated by means of a novel testing approach. A unique testing device, enabling nearly linear stand-alone cuts, was used. The specimens climatized to 6 different moisture content levels were machined within cutting velocities ranging from 5 to 80 m·s−1, at 5 cutting fibre angles from along to across the grain, and at different uncut chip thicknesses of up to 0.5 mm. The precise quartz sensor utilized for observing cutting forces enabled insights into the cutting mechanism involved while wood disintegration. Cutting velocity evolved as a key process parameter strongly influencing cutting force. Evaluation of uncut chip thickness showed a regression that was strongly influenced by particular force components. The friction force generated by “ploughing” the surface was relevant when cutting thin chips. In contrast, the part of force introduced by chip formation affected the process weightily in the case of cutting a thick chip. When cutting parallel to the grain lower forces were observed than cutting perpendicular to grain orientation. Obtained data supported the mathematical force prediction model establishment involving several parameters (e.g. cutting velocity, cutting fibre angle, uncut chip thickness, and moisture content). GRAPHICAL ABSTRACT
Effects of ambient temperature and humidity on body temperature and activity of heifers, and a novel idea of heat stress monitoring

Context Heat stress has led to a serious reduction in dairy cows production performance, thus increasing the stress of feeding and reproduction management. Aims Heat stress arises when cows are unable to dissipate excess body heat, we aimed to investigate the effects of ambient temperature (AT) and humidity on diurnal body temperature and activity. Methods For improving the technology for rearing dairy cows, the vaginal temperature (VT) and activity of 60 Holstein heifers in summer (n = 20), autumn (n = 20), and winter (n = 20) were measured using the oestrus monitoring system. Key results We found that VT fluctuated slightly (~38.22–38.32°C) when AT and temperature-humidity index (THI) were lower than 20°C and 68, respectively. However, when this threshold is reached, VT increased significantly with increasing AT and THI, whereas activity decreased significantly. Conclusions Heat stress may be caused when THI is above 68 and cow’s VT reaches 38.32°C. Evidently, when the THI exceeds 68 and VT is more than 38.32°C, suitable measures for reducing the effect of heat stress on the productivity of dairy cows should be taken. Implications The combined monitoring of VT and THI might provide accurate guidance for preventing and controlling heat stress.
Adaptive Differentiator-Based Predefined-Time Control for Nonlinear Systems Subject to Pure-Feedback Form and Unknown Disturbance

In this article, by utilizing the predefined-time stability theory, the predefined-time output tracking control problem for perturbed uncertain nonlinear systems with pure-feedback structure is addressed. The nonaffine structure of the original system is simplified as an affine form via the property of the mean value theorem. Furthermore, the design difficulty from the uncertain nonlinear function is overcome by the excellent approximation performance of RBF neural networks (NNs). An adaptive predefined-time controller is designed by introducing the finite-time differentiator which is used to decrease the computational complexity problem appeared in the traditional backstepping control. It is proved that the proposed control method guarantees all signals in the closed-loop system remain bound and the tracking error converges to zero within the predefined time. Based on the controller designed in this paper, the expected results can be obtained in predefined time, which can be illustrated by the simulation results.
Alexithymia, impulsivity and negative mood in relation to internet addiction symptoms in female university students

ABSTRACT Objective Alexithymia has been implicated as a risk factor for problematic substance use and other excessive behaviours including internet addiction . Impulsiveness has also been identified as a likely predisposing factor for excessive behaviours. However, as impulsivity is often elevated in alexithymia, the degree of independence of these factors in relation to excessive internet use is unclear. Method The present study assessed contributions of alexithymia, impulsivity and negative affect to variance in internet addiction symptoms in 116 internet-using female university students. Participants completed the following instruments online: demographics, Toronto Alexithymia Scale-20, Barratt Impulsiveness Scale-11, Internet Addiction Test and the Depression Anxiety Stress Scales-21. Results Measures were significantly intercorrelated in expected directions. Hierarchical regression indicated that although both alexithymia and impulsivity were highly significant predictors of internet addiction symptoms after controlling for demographic covariates, the contribution of alexithymia became nonsignificant after adding impulsivity to the model. The final model explained 37% of variance in internet addiction symptoms. Multiple mediation modelling indicated that both impulsivity and negative affect fully mediated the association of alexithymia with internet addiction symptoms. Conclusions Impulsivity and negative affect may account for the link between alexithymia and internet addiction symptoms in young women at university. KEY POINTS What is already known about this topic: Alexithymia and impulsivity have been linked to a variety of addictive behaviors including internet addiction. Alexithymia and impulsivity have been reported to independently predict excessive alcohol use in regression models. Alexithymia may reflect deficient interoception and corresponding poor internal awareness of overconsumption cues in alcohol use. What this topic adds: In female university students, alexithymia, impulsivity, and negative affect were significant positive predictors of internet addiction symptoms in a regression model. Alexithymia was no longer significant after adding impulsivity to the model. Multiple mediation modelling indicated that impulsivity and negative affect fully mediated the association of alexithymia with internet addiction symptoms.
“Who Would Bother Getting a Degree When You Would Be on the Exact Same Pay and Conditions . . .?” Professionalism and the Problem With Qualifications in Early Childhood Education and Care: An Irish Perspective

Although the literature is replete with research that indicates the importance of qualified and highly skilled practitioners in the provision of quality Early Childhood Education and Care (ECEC), challenges to the retention of highly skilled graduates and the establishment of a professional ECEC workforce persist. This study investigates the barriers that hinder practitioners from obtaining higher level ECEC qualifications. It presents findings from the perspectives of practitioners (n = 18) participating in the Early Childhood Care and Education (ECCE) Scheme using semi-structured interviews. This article is part of a doctoral study with practitioners and parents on quality in ECEC and the impact of technology on quality practice. Importantly, this article presents findings from the practitioner interviews as they relate to the barriers faced by practitioners in obtaining higher level qualifications. Findings indicate that practitioners value the role of qualifications in the provision of quality practice. Despite this, findings suggest that the likelihood of obtaining an ECEC degree is largely dependent on the practitioner’s financial situation. For example, in the absence of appropriate pay scales and occupational profiles, practitioners are forced to avail of social welfare services.
Automation: Uma Ferramenta para a Evolução de um Tradutor Automático Português-Libras com Corpus Colaborativo

Pessoas surdas comunicam-se naturalmente usando línguas viso-espaciais, denominadas Línguas de Sinais (LS). Apesar das línguas de sinais serem reconhecidas em muitos países como uma segunda língua oficial, nem sempre os conteúdos são gerados de forma acessível para esta comunidade. Com objetivo de minimizar esses impactos, pesquisas envolvendo tradução automática utilizando Aprendizagem Profunda ganham cada vez mais espaço na literatura. Porém, uma das principais barreiras para uso dessa estratégia é a necessidade de um corpus bilíngue, o que nem sempre é uma tarefa fácil de encontrar ou produzir. Nesse contexto, este trabalho apresenta uma ferramenta de automação de treinamentos para um tradutor automático Português-Libras. A solução comunica-se com um sistema colaborativo de traduções de sentenças Português-Libras, o WikiLibras, e alimenta o corpus de um tradutor automático para Libras, o VLibras, com objetivo de realizar treinamentos com um conjunto de dados cada vez mais robusto a cada iteração.
Effects of Workers Exposure to Nanoparticles Studied by NMR Metabolomics

In this study, the effects of occupational exposure to nanoparticles (NPs) were studied by NMR metabolomics. Exhaled breath condensate (EBC) and blood plasma samples were obtained from a research nanoparticles-processing unit at a national research university. The samples were taken from three groups of subjects: samples from workers exposed to nanoparticles collected before and after shift, and from controls not exposed to NPs. Altogether, 60 1H NMR spectra of exhaled breath condensate (EBC) samples and 60 1H NMR spectra of blood plasma samples were analysed, 20 in each group. The metabolites identified together with binning data were subjected to multivariate statistical analysis, which provided clear discrimination of the groups studied. Statistically significant metabolites responsible for group separation served as a foundation for analysis of impaired metabolic pathways. It was found that the acute effect of NPs exposure is mainly reflected in the pathways related to the production of antioxidants and other protective species, while the chronic effect is manifested mainly in the alteration of glutamine and glutamate metabolism, and the purine metabolism pathway.
Influence of Mg–Al Mixed Oxide Compositions on Their Properties and Performance in Aldol Condensation

The influence of chemical composition of Mg–Al mixed oxides on their properties and catalytic performance in aldol condensation of furfural and acetone was studied. Pure alumina, Mg–Al layered double hydroxides with a wide range of Mg/Al molar ratios from 0.5 to 15, and pure magnesia were prepared by the same synthesis method, and corresponding oxides were produced by calcination of the as-prepared samples at T = 450 °C. The physicochemical properties of the samples were investigated by XRD, N2 physisorption, SEM, CO2-TPD, and NH3-TPD, and their catalytic performance was evaluated in aldol condensation of furfural and acetone. SEM images revealed that the Al content in the samples influenced the size and the morphology of both large agglomerates and plate-like crystals. The CO2-TPD measurements proved that the concentration of basic sites and the distribution of their strengths was determined by the Mg/Al molar ratio in the Mg–Al mixed oxides. However, over the whole range of Mg/Al compositions studied he.
Mathematical Model of Physiological and Biochemical Indexes to Plant Growth–Defense Tradeoff in Salvia Miltiorrhiza

Background: Enzyme activities play a very important role in metabolism. Carbon (C) and nitrogen (N) are the two most basic elements for plant growth and development, and their mutual coupling makes C:N become an important index to explore plant element allocation and adaptation strategies. Although the key enzymes activity in carbon and nitrogen metabolism, and defense enzymes are often used to indexes of the physiological and biochemical characteristics of plants, the relationship between them and biomass still lacks understanding. In this paper, under the control condition, the biomass and 18 kinds of physiological and biochemical indexes were obtained through 24 groups experiments of the regenerated seedlings of Salvia miltiorrhiza by 9 endophytic fungi strains grafted. Results: The data were analyzed by descriptive statistical analysis, Lasso variable screening analysis and MLP neural network regression analysis. Results show that many physiological and biochemical indexes are related to biomass, and glutamine synthetase ( GS ),glutamate synthase ( GLS ), glutamate dehydroge nase ( GDH ), peroxidases (POD), catalase (CAT), soluble protein are the key factors which affect the biomass synthesis of Salvia miltiorrhiza . Conclusion: In this paper, it discusses the relationship between physiological and biochemical indexes and biomass in a comprehensive and systematic way by the framework of "Build-Design-Calculate-Test". Through rigorous logical reasoning process, the factors affecting the growth of Salvia miltiorrhiza are selected, and the mathematical model is established. It also provides a powerful tool for the comprehensive and systematic study of plant growth and the synthesis of effective components.
A new deep learning approach for classification of hyperspectral images: feature and decision level fusion of spectral and spatial features in multiscale CNN

Abstract Classification is the main field of hyperspectral data processing. To date, many methods are introduced to increase the accuracy of image classification. In recent years, various convolutional neural network models are proposed for hyperspectral image classification. This study puts forward a multiscale structure of convolutional neural networks that use several patches of different sizes to extract complex spatial features. Due to spatial features' effectiveness in improving the classification accuracy of hyperspectral images, the proposed framework integrates spatial features of three methods; morphological profiles, Gabor filter, and local binary pattern with spectral features at both the feature-level and decision-level. The experiments on three hyperspectral images, Indian Pine, Pavia University, and NCALM demonstrate the proposed method's efficiency. The final results show that the proposed method's overall classification accuracy is 6% higher than some other recent techniques.
Sustainable and Reusable Gelatin-Based Hydrogel “Jelly Ice Cubes” as Food Coolant. I: Feasibilities and Challenges

: Microbial cross-contamination caused by meltwater has been a serious food safety and quality concern. A new type of food coolant, “ jelly ice cubes ” (JICs), based on gelatin hydrogels, was designed and tested in this study to diminish meltwater while inheriting the high cooling e ﬃ ciency of traditional ice. The new zero-plastic JICs can prevent meltwater-caused cross-contamination with high a ﬀ ordability, recyclability, sustainability, and biodegradability. JICs based on 10% gelatin hydrogels achieved 265.35 J/g latent heat of fusion and cooling e ﬃ ciency comparable with traditional ice. JICs survived the normal pressure equivalent to a food load as tall as 1 m on top throughout the repeated freeze − thaw cycles. After each freeze − thaw cycle, JICs could be e ﬀ ectively rehydrated, cleaned, or sanitized with brief water or diluted bleach rinse. The application of JICs can potentially reduce water consumption in the food supply chain and food waste by controlling microbial contaminations. Since the feasibility was proven, future expectations for JICs in improved stability and heat-absorbing ability were proposed. groups on the C-terminus, amino groups on the N-terminus, and peptide bonds.
Compression and load balancing for efficient sparse matrix‐vector product on multicore processors and graphics processing units

We contribute to the optimization of the sparse matrix‐vector product by introducing a variant of the coordinate sparse matrix format that balances the workload distribution and compresses both the indexing arrays and the numerical information. Our approach is multi‐platform, in the sense that the realizations for (general‐purpose) multicore processors as well as graphics accelerators (GPUs) are built upon common principles, but differ in the implementation details, which are adapted to avoid thread divergence in the GPU case or maximize compression element‐wise (i.e., for each matrix entry) for multicore architectures. Our evaluation on the two last generations of NVIDIA GPUs as well as Intel and AMD processors demonstrate the benefits of the new kernels when compared with the optimized implementations of the sparse matrix‐vector product in NVIDIA's cuSPARSE and Intel's MKL, respectively.
Improving the Assessment of Teaching Effectiveness With the Nonequivalent Dependent Variables Approach

Introduction: Assessing teaching effectiveness is relevant for improving one’s teaching and for moving through the tenure process; however, the validity of assessment methods, such as Student Evaluations of Teaching (SET), have been heavily criticized. Statement of the Problem: Using a one–group pretest–posttest design and assessing learning over the semester has several advantages over SET; however, one drawback is in making conclusions about the cause of changes in the post-test. A change could be due to learning in the semester, maturation, history, or even a testing effect. Literature Review: To improve the inferential quality of teaching assessment, a nonequivalent dependent variable (DV) design is highly advantageous. A nonequivalent DV is an outcome that is not the target of the intervention yet responds to the same contextually relevant factors. Teaching Implications: By using a nonequivalent DV design, there might be an increase from the beginning of the semester to the end of the semester in the main DV, but no increase in the nonequivalent DV, which provides a stronger argument that the change in the main DV is due to a true learning effect. Conclusion: Using nonequivalent DV methodology improves inferential quality and is easily implemented.
Therapeutic metaphors and personal meanings in group poetry therapy for people with schizophrenia

ABSTRACT This article concerns the therapeutic potential of metaphor in group poetry therapy, concentrating on the poetry therapy process of people diagnosed with schizophrenia. The data was collected in a one-year poetry therapy group. The main questions were: (1) What kind of therapeutic potential can metaphors offer in group poetry therapy? (2) What are the personal meanings and evaluations that the participants give to the therapy process and its effects on their lives? (3) What are the most significant elements in poetry therapy from the viewpoint of the client? The analysis was based on the Grounded theory method. The results showed that the most significant therapeutic factors of the process were social interaction, safety, and written self-expression. Writing in a group setting, especially through collaborative writing, had many positive effects on the clients. It allowed them to experience life’s worth raising their hope. Metaphors and collaborative writing made it possible to discuss difficult personal experiences.
Basic Residue Clusters in Intrinsically Disordered Regions of Peripheral Membrane Proteins: Modulating 2D Diffusion on Cell Membranes

A large number of peripheral membrane proteins transiently interact with lipids through a combination of weak interactions. Among them, electrostatic interactions of clusters of positively charged amino acid residues with negatively charged lipids play an important role. Clusters of charged residues are often found in intrinsically disordered protein regions, which are highly abundant in the vicinity of the membrane forming what has been called the disordered boundary of the cell. Beyond contributing to the stability of the lipid-bound state, the pattern of charged residues may encode specific interactions or properties that form the basis of cell signaling. The element of this code may include, among others, the recognition, clustering, and selective release of phosphatidyl inositides, lipid-mediated protein-protein interactions changing the residence time of the peripheral membrane proteins or driving their approximation to integral membrane proteins. Boundary effects include reduction of dimensionality, protein reorientation, biassing of the conformational ensemble of disordered regions or enhanced 2D diffusion in the peri-membrane region enabled by the fuzzy character of the electrostatic interactions with an extended lipid membrane.
Numerical investigation on the flow around an inclined prolate spheroid

Numerical simulations are performed for the flow around an inclined 5:2 prolate spheroid in a uniform freestream. The Reynolds number (Re = 300, 500, 700, and 1000) and incidence angle (α = 0°–90°) are considered as significant parameters affecting the wake transitions, where α = 0° indicates flow parallel to the major axis of the prolate spheroid, and the Re is based on the inflow velocity U0 and the volume-equivalent sphere diameter De of the spheroid. In the range considered of Re and α, eight flow regimes are identified: (i) steady axisymmetric (SA) flow regime; (ii) steady planar symmetric flow regime; (iii) steady asymmetric (SAS) flow regime; (iv) periodic planar symmetric flow regime with non-zero mean lift or “Zig-zig-like” (Zz-like) mode; (v) periodic asymmetric flow regime with double-sided vortex shedding; (vi) multi-periodic asymmetric flow regime with double-sided vortex shedding and low frequency modulation (MPADL); (vii) multi-periodic asymmetric flow regime with single-sided vortex shedding and low frequency modulation (MPASL); and (viii) weakly chaotic state. Three of them are new and first reported, i.e., SAS, MPADL, and MPASL modes. The wake structure of the Zz-like mode is different from that of the zig-zig mode in the sphere/disk wake with a pair of streamwise vortices extending to the near wake. It is found that the elongated body can delay the onset of unsteadiness at small incidence angles. A flow regime map in the considered (Re, α) space is then provided. Finally, the physical mechanisms of the low-frequency phenomena observed at different wake modes are explored.
Algebra Instruction for Students with Learning Disabilities in the Era of Common Core

The Common Core State Standards in Mathematics (CCSSM) were released more than 10 years ago. This set of standards outlines the mathematics that all students should know and be able to do to prepare them for post-secondary education and employment. Students with learning disabilities (LD) continue to underperform in relation to their peers without disabilities in secondary mathematics. As high school Algebra I is a required course for the majority of students, research-based instructional practices should be utilized to support students with LD in Algebra I. This article summarizes recent research on instructional practices for teaching algebra content that aligns to the CCSSM. Specifically, three types of instructional practices have been found to promote progress in the high school algebra content: (a) concrete-representational-abstract integration, (b) virtual manipulative instruction, and (c) gestures and diagrams.