Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterization of High Temperature Creep Properties in Recrystallized 12Cr-ODS Ferritic Steel Claddings

The high temperature strengthening mechanism of previously manufactured 12Cr-ODS ferritic steel claddings was clarified. In the recrystallized 12Cr-2W-0.3Ti-0.24Y2O3-ODS ferritic steel cladding, αY2TiO5 type complex oxide formation was responsible for the drastic reduction of oxide particle size and the resulting shortened distance between particles, which led to superior internal creep rupture strength at 973 K because of the high resistance to gliding dislocation. Internal creep deformation was considered to be controlled by the grain boundary sliding associated with grain morphology: the near Σ11, Σ and Σ19 coincidence boundaries with a (110) common axis.
On the Impact of the Caribbean Counter Current in the Guajira Upwelling System

The variability of La Guajira upwelling system, in the south-central Caribbean Sea, is strongly influenced by the intensity and location of the atmospheric Caribbean Low-Level Jet (CLLJ), a near-surface branch of the easterlies, as well as by the regional ocean circulation. During favorable conditions (i.e., strong easterlies blowing almost parallel to the coast), upwelling is enhanced and a large amount of primary productivity occurs in La Guajira area. In contrast, during relatively mild wind conditions, the CLLJ is misaligned to the coast and the Caribbean Counter Current (CCC, locally also known as the Darien Current), which forms as a branch from the Panama-Colombia Gyre, flows northeastward over the continental shelf advecting waters from the southwestern Caribbean basin toward La Guajira. The CCC has a clear signature at the surface layer that extends from the Darien Gulf toward La Guajira peninsula during mild wind periods, while disappears during the months of strong winds. The direction and the magnitude of the easterlies, and more specifically of the CLLJ, control the position and pathway of the CCC, which extends more than 900 km in the southern Caribbean Sea during May, June, August, September, and October. The high concentration of chlorophyll-a at the sea surface evidenced by satellite-based color images is semi-seasonally modulated by the CLLJ, which during its relaxation phase allows the irruption of the CCC toward the east up to La Guajira.
The Mediating Role of Stress Perception in Pathways Linking Achievement Goal Orientation and Depression in Chinese Medical Students

Mental health problems are frequent obstacles in medical students’ careers as doctors. Given that previous studies overlook the mediation of stress perception, the current study expanded previous goal orientation researches by addressing an unexplored mechanism. This study aims to examine the mediational roles of stress perception (perceived stressors and stress-related cognition) on the relationship between achievement goal orientation and depression in medical students. A total of 1,015 Chinese 2-year medical students completed a multi-section questionnaire. Hypotheses were examined by structural equation modeling. The findings suggest that performance-avoidance goal orientation and perceived stressors both demonstrated direct facilitative effects on depression, whereas stress-related cognition demonstrated direct obstructive effects on depression. Both perceived stressors and stress-related cognition mediated the relationship between achievement goal orientation and depression. The findings spark a new perspective on motivational intervention that assist students in adopting mastery-approaching strategy as well as ways of coping with stressful academic situations. Identifying students with achievement goal orientation and providing them with the appropriate supportive services may help them to manage stress and mitigate or prevent depression.
A distinct population of heterogeneously color-tuned neurons in macaque visual cortex

Diverse color tuning in V4 receptive fields points to its possible role in encoding complex color stimuli in natural environment. Color is a key feature of natural environments that higher mammals routinely use to detect food, avoid predators, and interpret social signals. The distribution of color signals in natural scenes is widely variable, ranging from uniform patches to highly nonuniform regions in which different colors lie in close proximity. Whether individual neurons are tuned to this high degree of variability of color signals is unknown. Here, we identified a distinct population of cells in macaque visual cortex (area V4) that have a heterogeneous receptive field (RF) structure in which individual subfields are tuned to different colors even though the full RF is only weakly tuned. This spatial heterogeneity in color tuning indicates a higher degree of complexity of color-encoding mechanisms in visual cortex than previously believed to efficiently extract chromatic information from the environment.
Levulinic acid production from wood with green solvents

Abstract In this work, protic ionic liquid, 1-methylimidazolium hydrogen sulfate (HMIMHSO4) and gamma-valerolactone (GVL) were explored with respect to their effects on levulinic acid production directly from cotton stalks and pine using the acidic catalyst, CrCl3.6H2O in a hydrothermal reactor. GVL as a biomass-derived solvent resulted in higher yields of levulinic acid compared to HMIMHSO4 which was attributed to the higher lignin depolymerization capacity of the solvent and GVL’s capability for stabilization of the solvated protons. The increasing water content of the media from 10% to 20% enhanced the production and the yields. GVL gave the maximum levulinic acid concentration and yield from pine; 21.4 g/L and 78%, respectively when the reaction was conducted at 180 °C and 10% biomass loading with 20% water and 0.1 M CrCl3.6H2O for 4 h.
Responsiveness to bepridil predicts atrial substrate in patients with persistent atrial fibrillation

The low voltage zone (LVZ) detected with three‐dimensional electroanatomical mapping is a surrogate marker of atrial scar in patients with persistent atrial fibrillation (PeAF) and is associated with poor clinical outcomes after catheter ablation. However, fewer studies have reported the relationship between responsiveness to antiarrhythmic drugs and the LVZ.
Weighted ensemble networks for multiview based tiny object quality assessment

As demand for intelligent manufacturing continues to grow, tiny object quality assessment (TOQA) is becoming increasingly importance in industrial automation. Recently, visual‐based TOQA has attracted an increasing attention, since the physical appearance is the foremost assessment index for evaluating the tiny object quality. It is exhausted and challenging to determine the quality of tiny object by manual visual inspection, and thus some machine vision systems are developed for automatic TOQA. Existing systems often use a limited number of cameras to capture the image of fallen tiny object, and thus may be not reliable since the tiny object may be unsound (such as cracked or damaged) in an invisible side. In this article, we develop a novel system for automatic TOQA that captures images of tiny object from multiple (more than two) view points, and propose a novel method termed weighted ensemble network (WENet) to effectively integrate the information of different views. In particular, convolutional neural networks (CNNs) are adopted to extract features from the images of different views. Then the multiview features are weighted combined for tiny object quality prediction. Traditional ensemble approaches usually directly applying average or voting to the prediction results of different views, or learn fixed weights to combine the results. Different from these approaches, the weights are adaptively determined in our method according to the quality of the captured image, since the features extracted from a low‐quality (e.g., blurred) image should contribute less to the final prediction. Handcrafted features and deep features are integrated in a sophisticated way in our method, and we empirically demonstrate the effectiveness of our method on grain quality assessment by investigating different CNN architectures for feature extraction and comparing with the conventional ensemble approaches.
From Digitized Sources to Digital Data: Behind the Scences of (Critically) Enriching a Digital Heritage Collection

Digitally available repositories are becoming not only more and more widespread but also larger and larger. Although there are both digitally-born collections and digitised material, the digital heritage scholar is typically confronted with the latter. This immediately presents new challenges, one of the most urgent being how to ﬁnd the meaningful elements that are hidden underneath such unprecedented mass of digital data. One way to respond to this challenge is to contextually enrich the digital material, for example through deep learning. Using the enrichment of the digital heritage collection ChroniclItaly 3.0 [10] as a concrete example, this article discusses the complexities of this process. Speciﬁcally, combining statistical and critical evaluation, it describes the gains and losses resulting from the decisions made by the researcher at each step and it shows how in the passage from digitised sources to enriched material, most is gained (e.g., preservation, wider and enhanced access, more material) but some is also lost (e.g., original layout and composition, loss of information due to pre-processing steps). The article concludes that it is only through a critical approach that the digital heritage scholar can successfully meet the interpretive challenges presented by the digital and the digital heritage sector fulﬁl the second most important purpose of digitisation, that is to enhance access.
Sensory Quality of Culinary Pork Meat in Relation to Slaughter and Technological Value

The aim was to estimate sensory pork quality in relations to its carcass and technological value. The research was executed on 57 hogs. The studied meat from hogs were characterized by appropriate slaughter and technological value (pH, drip loss, cooking and technological yield). The large variability of visual quality of meat (colour, marbling) was observed. The appropriate visual quality of meat in relationship to marbling was originated from carcass by meatiness above 56.7%. These meat samples were also characterized by relatively high drip loss (> 5.95%) in comparison to meat samples originated from carcass with meatiness below 56%, although the relationship was not statistically significant. The mean value of meatiness 56.3% provided a high sensory eating quality of meat after heat treatment. The eating quality was mainly related to flavour and texture. The expected quality of raw meat based on visual evaluation was not correlated with high eating quality (experienced quality) of meat after heat treatment.
Detecting Sarcasm in News Headlines

The use of sarcasm dates as far back as communication goes. Sarcasm is expressed in words, facial expression and can be noticed in the intonation of voice. In this digital age, sarcastic comments are passed everyday, via tweets, comment sections of diﬀerent social media outlets, and even in news headlines. Some of these headlines can be misunder-stood and taken to mean something diﬀerent than the original intentions. This leads to a need to detect sarcasm especially in the news and on social media. Detection of sarcasm from text has its challenges because text lacks intonation and deﬂection of voice that occurs when a sarcas-tic statement is made vocally by a human. This paper concentrates on the eﬀect of diﬀerent feature encoding techniques applied to text for feature extraction for machine learning models. A deep learning model is also applied and the results are compared. Prior to feature extraction, data pre-processing techniques like tokenization, removal of stop-words and punctuation are applied by researchers in any work involving text analysis. These pre-processing techniques are widely used and accepted and are also applied in this project. Diﬀerent feature extraction methods like Count Vectorizer, Term Frequency-Inverse Document Frequency and word embedding were implemented in this experiment. The Support Vector Machine, Naive Bayes and Logistic Regression were the traditional machine learning algorithms used in this research. Convolutional Neural Network was also used. Results of these algorithms are recorded in this paper and these include the F1-score, precision, recall and the accuracy scores. The results of these diﬀerent algorithms for the methods of feature extraction examined in this paper show that a combination of more than one technique is better suited for the purpose of classiﬁcations. The results of this paper show
Chatbot Based Behaviour Analysis for Obesity Support Platform

The challenge created by the health problem of rising obesity rates requires novel approaches to solve. This paper presents an innovative approach in the form of a conversational platform aimed at helping users deal with with health issues associated with obesity. The chatbot platform enables collection of personal data from users to be analysed via natural language processing and behavioural analysis to provided tailored solutions for each user based on their current states and psychological traits. The gathered and analysed data is accessible. This platform developed using Microservices architecture and chatbot technology. User can interact with the chatbot to generate personal chat data stored in the platform. The collected chat data will be used for natural language processing and behaviour analysis, along with other available data, to create a customized user model. The gathered and analysed data is accessible and usable for Health Care professionals as a mechanism to encourage healthier nutrition, and the user can beneﬁt from the platform by getting feedback and support on their methods for improving their eating and physical activity habits by way of the chatbot.
Handcraft and Automatic Approaches for the Recognition of Leukemia Images

In this paper, we analyze how handcraft and automatic approaches frequently can be used in the recognition of leukemia images. The visual recognition of subtypes of leukemia cells is a difficult problem in medical area. For this reason, the visual analysis is a feasible option when advanced techniques for diagnosis are not available. Additionally, the problem of determining a logic sequence of the process of recognition is equal or more important that the solution itself, which implies to know the advantages and drawbacks of the available approaches to solve a particular problem of visual recognition. Thus, in this paper we present two approaches that allow us become aware of the use of particular techniques in problems such as leukemia cell recognition.
Dependence of alkyl-substituent length for bulk heterojunction solar cells utilizing 1,4,8,11,15,18,22,25-octaalkylphthalocyanine

Bulk heterojunction organic thin-film solar cells utilizing soluble phthalocyanine derivatives, 1,4,8,11,15,18,22,25-octaalkylphthalocyanine (CnPcH2, n = 6, 7, 9, 10), were investigated. Two broad peaks existing in the external quantum efficiency spectra almost correspond to the Q-band and B-band of CnPcH2. The solar cell utilizing C6PcH2 had the best photovoltaic properties as evidenced by open-circuit voltage, short-circuit current density, fill factor, and energy conversion efficiency. Almost the same photovoltaic properties were observed in the solar cells utilizing C9PcH2 and C10PcH2. We discuss the photovoltaic properties by taking into consideration the crystal structure and electronic state of CnPcH2 from the results of the absorbance spectra, X-ray diffraction measurement, and polarization microscope observation.
Growth of highly tensile-strained Ge on relaxed InxGa1−xAs by metal-organic chemical vapor deposition

Highly tensile-strained Ge thin films and quantum dots have the potential to be implemented for high mobility metal-oxide-semiconductor field-effect transistor channels and long-wavelength optoelectronic devices. To obtain large tensile strain, Ge has to be epitaxially grown on a material with a larger lattice constant. We report on the growth of tensile-strained Ge on relaxed InxGa1−xAs epitaxial templates by metal-organic chemical vapor deposition. To investigate the methods to achieve high quality Ge epitaxy on III–V semiconductor surfaces, we studied Ge growth on GaAs with variable surface stoichiometry by employing different surface preparation processes. Surfaces with high Ga-to-As ratio are found to be necessary to initiate defect-free Ge epitaxy on GaAs. With proper surface preparation, tensile-strained Ge was grown on relaxed InxGa1−xAs with a range of In content. Low growth temperatures between 350 and 500 °C suppress misfit dislocation formation and strain relaxation. Planar Ge thin films with .
Selective Adsorption of Dibenzothiophenes on Activated Carbons with Ag, Co, and Ni Species Deposited on Their Surfaces

Adsorption of dibenzothiophene (DBT) and 4,6-dimethyldibenzothiophene (4,6-DMDBT) from simulated diesel fuel with 20 ppm total concentration of sulfur was investigated on three polymer-derived carbon-containing silver, cobalt, and nickel species. The initial and exhausted carbons were characterized using adsorption of nitrogen, thermal analysis, XRD, SEM, and TEM. The selectivities for DBT and 4,6-DMDBT adsorption were calculated with reference to naphthalene. The results showed a good adsorption capacity of the carbons studied. The adsorbents remove DBT and 4,6-DMDBT selectively from model diesel fuel. Metal species contribute to an increase in the number of active centers, which enable adsorption of DBT and 4,6-DMDBT on the surface. That surface would not be used to the same extent when only dispersive forces were involved. Nanosize metallic silver particles not only attract DBT and 4,6-DMDBT but also catalyze their oxidation.
High critical current densities in Cu-sheathed MgB2 formed from a mechanically-alloyed precursor

Mechanical alloying is used to produce a metallic precursor for MgB2 formation. Micron-scale mixing of magnesium and boron powders allows the MgB2 formation reaction to proceed at as low as 450 °C, with high-quality material formed in an hour at 600 °C. These low reaction temperatures allow the reaction to be performed in situ in a copper sheath. Critical current densities, calculated from a full critical-state simulation of magnetization hysteresis loops, are up to 7×105 A/cm2 at 13.6 K and 1×105 A/cm2 at 30 K, in zero applied field.
Successive linearisation analysis of unsteady heat and mass transfer from a stretching surface embedded in a porous medium with suction/injection and thermal radiation effects

In this study, we investigate the application of the new successive linearisation method (SLM) to the problem of unsteady heat and mass transfer from a stretching surface embedded in a porous medium with suction/injection and thermal radiation effects. The governing nonlinear momentum, energy and mass transfer equations are successfully solved numerically using the SLM approach coupled with the spectral collocation method for iteratively solving the governing linearised equations. Comparison of the SLM results for various flow parameters against numerical results and other published results, obtained using the homotopy analysis method (HAM) and Runge–Kutta methods, for related problems indicates that the SLM is a very powerful tool which is much more accurate and efficient than other methods. The SLM converges much faster than the traditional methods like the HAM and is very easy to implement.
Different behavior of iron(III) and aluminum(III) salts to coagulate silica particle suspension

The different coagulation-flocculation behavior of iron(III) and aluminum(III) to coagulate silica particle suspension with four coagulants - FeCl 3 , Fe 2 (SO 4 ) 3 , AlCl 3 , and in our laboratory produced polyaluminum chloride PACl-2.0 - was investigated through studying particle property changes and coagulation efficiency, for example, variations in zeta potential of particles, particle number, average particle diameter, particle size distribution, and residual turbidity of the supernatant water. Influences of flocculation intensity and pH value on the coagulation-flocculation process were also studied. The results suggest that, under the test conditions, among these four coagulants FeCl 3 possesses an obviously stronger ability to form larger flocs and to remove turbidity, on the other hand, PACl-2.0 obviously showed a better charge neutralization ability.
Controlled Over-Expression of AtDREB1A Enhances Tolerance against Drought and Salinity in Rice

Engineering transcription factors (TF) hold promise in enhancing abiotic stress tolerance in plants. In this study, one of the popular rice varieties of South India, namely ADT 43, was engineered with a TF AtDREB1A driven by a stress-inducible rd29A promoter. PCR and Southern hybridization were employed to confirm the integration and copy number of the transgene. Transgenic lines (T1) of ADT 43 showed enhanced tolerance to drought and salinity compared to the non-transgenic ADT 43. Transgenic lines were found to maintain higher RWC %, lower leaf temperature, and partially closed stomata, enabling better survival under stress conditions. qRT-PCR analysis revealed the strong induction of AtDREB1A transcripts during drought. Transgenic lines of ADT 43 exhibited increased germination and retention of chlorophyll in their leaves under salinity. Evaluation of transgenic lines under transgenic screen house conditions revealed that line # A16 exhibited on par agronomic performance against its non-transgenic counterpart under normal conditions. Under drought, non-transgenic ADT 43 showed >20% reduction in the total number of spikelets per panicle, whereas transgenic line # A16 registered only a 2% reduction. Non-transgenic ADT 43 recorded 80% yield reduction under drought, whereas line # A16 recorded only 54% yield loss. The above results demonstrated the effectiveness of controlled expression of DREB1A in regulating dehydration responses in rice.
The Effect of Mobile User Typology on Mobile Learning Adoption in Higher Education

: Mobile user typology is absent from popular models for mobile learning adoption though understanding such typology can help with design of learning. This paper explores the salient mobile user typology by applying latent class analysis to reported use of mobile phone features collected from students at six university campuses in four countries (Barbados, Guyana, Jamaica, Trinidad and Tobago). It also relates the user types to behavioural intention to adopt mobile learning within a structural equation modelling framework. The results indicate four mobile user types which are distributed differently over the campus-territory groups and to which age, sex, programme level and programme type of the students are significantly related. Furthermore, mobile user typology is related to behavioural intention to adopt mobile learning and this avails it as a candidate for inclusion in models used for mobile learning adoption. There is some extent of cross-national specificity of mobile user typology though some user categories seem to be more generalisable