Miracle-dz/UniFAR-FTUs huggingface dataset:
Applying Control-Value Theory and Unified Theory of Acceptance and Use of Technology to Explore Pre-service Teachers’ Academic Emotions and Learning Satisfaction

Academic emotions refer to the emotions related to achievement activities or outcomes. Academic emotions are directly related to learning performance and have been recognized as critical to learners’ learning satisfaction and learning effectiveness in the online learning context. This study aimed to explore the relationship between academic emotions and learning satisfaction and their underlying mechanisms in massive open online courses (MOOCs) learning context using mediation models. This study adhered to the theoretical frameworks of the control-value theory (CVT) and the unified theory of acceptance and use of technology (UTAUT). Participants were 283 pre-service teachers who volunteered from a normal university in Southwestern China. Results revealed that: (a) academic emotions did not predict learning satisfaction; (b) learning interest and technology acceptance fully mediated the influence of academic emotions on learning satisfaction; (c) the four dimensions of technology acceptance did not mediate the relationship between academic emotions and learning satisfaction. This study integrated CVT and UTAUT models, and the results emphasized the importance of academic emotions and learning satisfaction in CVT and provision of additional support for UTAUT. Therefore, these findings have significant implications for improving the quality of MOOCs in the post-pandemic era.
A New Look at Infant Problem-Solving: Using DeepLabCut to Investigate Exploratory Problem-Solving Approaches

When confronted with novel problems, problem-solvers must decide whether to copy a modeled solution or to explore their own unique solutions. While past work has established that infants can learn to solve problems both through their own exploration and through imitation, little work has explored the factors that influence which of these approaches infants select to solve a given problem. Moreover, past work has treated imitation and exploration as qualitatively distinct, although these two possibilities may exist along a continuum. Here, we apply a program novel to developmental psychology (DeepLabCut) to archival data (Lucca et al., 2020) to investigate the influence of the effort and success of an adult’s modeled solution, and infants’ firsthand experience with failure, on infants’ imitative versus exploratory problem-solving approaches. Our results reveal that tendencies toward exploration are relatively immune to the information from the adult model, but that exploration generally increased in response to firsthand experience with failure. In addition, we found that increases in maximum force and decreases in trying time were associated with greater exploration, and that exploration subsequently predicted problem-solving success on a new iteration of the task. Thus, our results demonstrate that infants increase exploration in response to failure and that exploration may operate in a larger motivational framework with force, trying time, and expectations of task success.
Development and Internal Validation of a Preoperative Prediction Model for Sentinel Lymph Node Status in Breast Cancer: Combining Radiomics Signature and Clinical Factors

Purpose To develop and internally validate a nomogram combining radiomics signature of primary tumor and fibroglandular tissue (FGT) based on pharmacokinetic dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and clinical factors for preoperative prediction of sentinel lymph node (SLN) status in breast cancer patients. Methods This study retrospectively enrolled 186 breast cancer patients who underwent pretreatment pharmacokinetic DCE-MRI with positive (n = 93) and negative (n = 93) SLN. Logistic regression models and radiomics signatures of tumor and FGT were constructed after feature extraction and selection. The radiomics signatures were further combined with independent predictors of clinical factors for constructing a combined model. Prediction performance was assessed by receiver operating characteristic (ROC), calibration, and decision curve analysis. The areas under the ROC curve (AUCs) of models were corrected by 1,000-times bootstrapping method and compared by Delong’s test. The added value of each independent model or their combinations was also assessed by net reclassification improvement (NRI) and integrated discrimination improvement (IDI) indices. This report referred to the “Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis” (TRIPOD) statement. Results The AUCs of the tumor radiomic model (eight features) and the FGT radiomic model (three features) were 0.783 (95% confidence interval [CI], 0.717–0.849) and 0.680 (95% CI, 0.604–0.757), respectively. A higher AUC of 0.799 (95% CI, 0.737–0.862) was obtained by combining tumor and FGT radiomics signatures. By further combining tumor and FGT radiomics signatures with progesterone receptor (PR) status, a nomogram was developed and showed better discriminative ability for SLN status [AUC 0.839 (95% CI, 0.783–0.895)]. The IDI and NRI indices also showed significant improvement when combining tumor, FGT, and PR compared with each independent model or a combination of any two of them (all p < 0.05). Conclusion FGT and clinical factors improved the prediction performance of SLN status in breast cancer. A nomogram integrating the DCE-MRI radiomics signature of tumor and FGT and PR expression achieved good performance for the prediction of SLN status, which provides a potential biomarker for clinical treatment decision-making.
Systemic Therapy for Microsatellite Instability Small Bowel Adenocarcinoma With Mesenteric Vascular Embolism as Initial Symptom: A Case Report

Background: Small bowel adenocarcinoma are relatively rare tumors of the digestive system. Due to the lack of specific screening methods, patients are often diagnosed at an advanced stage. At present, there is no specific surgical guidance and chemotherapy regimen for small bowel adenocarcinoma. Here, we report a rare small bowel adenocarcinoma case with mesenteric vascular embolization and microsatellite instability, in which palliative surgery combined with chemotherapy and anti-Programmed cell death protein 1(PD-1) therapy resulted in complete remission. Case Presentation: The patient was a 55-year-old man who was admitted for suspected small bowel adenocarcinoma combined with incomplete ileus, mesenteric vascular occlusion and distant metastasis. We performed palliative surgery to remove adenocarcinoma as well as relieve obstruction. Then according to the pathological and immunohistochemical results (Stage IV and microsatellite instability), we used XELOX regimen combined with anti-PD-1 therapy. In last 2 years follow up, this patient achieved complete remission. Conclusions: The possibility of small intestinal tumor should be considered in patients with mesenteric vascular obstruction. PD-1 blockade is an effective therapy for small bowel adenocarcinoma with microsatellite instability.
SARS-CoV-2 Infection in Pregnancy: Clinical Signs, Placental Pathology, and Neonatal Outcome—Implications for Clinical Care

Introduction: The current COVID-19 pandemic has been associated with high rates of mortality and significant morbidity. Both the risk of infection for pregnant women and the risk of vertical transmission have been evaluated, and the presence of the SARS-CoV-2 virus has been demonstrated both in the placenta and in the amniochorionic membranes. However, the actual effects of this pathogen on pregnancy and on placental morphology are still unclear. Objective: To describe histopathologic findings in the placentas of women with SARS-CoV-2 infection during pregnancy and their correlation with clinical signs and perinatal outcome. Methods: Placental tissues from pregnant women with SARS-CoV-2 infection delivering between March 2020 and February 2021 were analyzed. Results: One hundred six placentas from women with SARS-CoV-2 infection during pregnancy who delivered in Fondazione Policlinico A. Gemelli were examined. Most of them were asymptomatic. All neonates had available test results for SARS-CoV-2 and only one resulted positive. Placental tissues mainly showed signs of maternal vascular malperfusion and of placenta injury in terms of syncytial node increase (96.2%), villar agglutination (77.3%), neointimal hyperplasia (76.4%), excessive fibrin deposition (43.3%), and chorangiosis (35.8%). No significant differences in the frequency of the histopathological lesions were observed according to maternal symptoms. Conclusion: Looking to placental tissues from SARS-CoV-2 positive women at the screening performed close to delivery, placental injuries could be detected without any correlation with fetal and neonatal outcomes. We hypothesize that short latency between SARS-CoV-2 infection and delivery is the main reason for these observations.
Morphological Description and Ethnobotanical Review of the Orphan Crop Myin-Hkwa (Centella asiatica L.) From Myanmar

Centella asiatica is a medicinal herb commonly known as Asiatic pennywort or gotu kola. The species is valued for its medicinal and nutritional properties. It is a perennial plant with leaves and stems that can be consumed as a green leafy vegetable. It is used as a folk remedy to cure various mild and chronic diseases due to its anti-rheumatic, antipyretic, antibacterial, antiviral, and anti-inflammatory effects, and as a mental rejuvenator. Although the species is widely distributed throughout the tropics and subtropics, its recognition was limited. The morphological description of C. asiatica is not well-documented in Myanmar, in Burmese or other local languages. Plant assessment via morphological markers is one of the ultimate methods for the primary description and characterization of their phenotypic traits. The objectives of this study were focused on the description of Myanmarese C. asiatica grown in Japan through morphological markers and a brief overview of its ethnobotanical use in Asia. Morphological characterization revealed the quantitative and qualitative differences regarding several traits among assessed C. asiatica samples. Furthermore, the study can provide information on the primary C. asiatica cultivation system in Japan, as it can be a potentially new and economically important crop for the Japanese market.
A multi-criteria design framework for the synthesis of complex pressure swing adsorption cycles for CO2capture

Pressure Swing Adsorption (PSA) is the most efficient option for middle scale separation processes. PSA is a cyclic process whose main steps are adsorption, at high pressure, and regeneration of the adsorbent, at low pressure. The design of PSA cycles is still mainly approached experimentally due to the computational challenges posed by the complexity of the simulation and by the need to detect the performance at cyclic steady state (CSS). Automated tools for the design of PSA processes are desirable to allow a better understanding of the the complex relationship between the performance and the design variables. Furthermore, the operation is characterised by trade-o�ffs between conflicting criteria. A multi-objective flowsheet design framework for complex PSA cycles is presented. A suite of evolutionary procedures, for the generation of alternative PSA con�figurations has been developed, including simple evolution, simulated annealing as well as a population based procedure. Within this evolutionary procedure the evaluation of each cycle confi�guration generated requires the solution of a multi-objective optimisation problem which considers the conflicting objectives of recovery and purity. For this embedded optimisation problem a multi-objective genetic algorithm (MOGA), with a targeted fi�tness function, is used to generate the approximation to the Pareto front. The evaluation of each alternative design makes use of a number of techniques to reduce the computational burden. The case studies considered include the separation of air for N2 production, a fast cycle operation which requires a detailed di�ffusion model, and the separation of CO2 from flue gases, where complex cycles are needed to achieve a high purity product. The novel design framework is able to determine optimal configurations and operating conditions for PSA for these industrially relevant case studies. The results presented by the design framework can help an engineer to make informed design decisions.
Modelling the fluid drainage through primary lymphatic valves

This study investigates the fluid flow through tissues where lymphatic drainage occurs. Lymphatic drainage relies on two unidirectional valve systems, primary and secondary. The primary system is located in the initial lymphatics with, it is presumed, overlapping endothelial cells around the circumferential lining of lymphatic capillaries which act as unidirectional valves. The secondary lymphatic system is located in the lumen of the collecting lymphatics and is well studied in contrast to the primary system. We propose two models for the drainage of fluid by the lymphatic system that includes the primary valve system. The analysis identifies four key areas that affect lymphatic drainage. These are: the regular tissue deformations, the mechanics of the primary lymphatic valves, the fluid flow through the interstitium and that through the walls of blood capillaries. The models outline a new way of modelling the primary valve system that appears to be more relevant to experimental studies than previous models. The first model presented in this thesis describes a permeable membrane around a blood capillary, an elastic primary lymphatic valve and the interstitium lying between the two. Here we pay special attention to the mechanics of the primary valve system, by assuming that lymphatic endothelial cells (primary valve system) deflect into the lumen (allowing fluid drainage) in response to pressure differences between the interstitium and the lumen. The model predicts a piecewise linear relation between the drainage flux and the pressure difference between the blood and lymphatic capillaries. The second model presented in this thesis includes the regular tissue deformations in modelling lymphatic drainage. We propose a 'sliding door' theory of how lymphatic drainage occurs, which we base upon the premise that when the interstitium expands (due to excess fluid)the surrounding matrix pulls open the lymphatic valves creating a gap for the interstitial flid to drain into the lumen. The model predicts that after a certain number of valve cycles (close to open to close)the system relaxes to a steady state, in which the lymphatic valve stays open.
Development of Small Intestinal Submucosa as Biomaterial in Tissue Engineering

Small intestinal submucosa as a kind of natural ECM was widely studied as biological material from now on. Attachment on SIS, the proliferation, migration and differentiation of numerous cells were found be influence. Due to its excellent biocompatibility, biomechanical properties and biological activity, SIS had been extensive used as biomaterial in regenerative medicine. This article reviews the recent progress in the characterization and medical application of SIS respectively.
Rapid encoding of task regularities in the human hippocampus guides sensorimotor timing

The brain encodes the statistical regularities of the environment in a task-specific yet flexible and generalizable format. Here, we seek to understand this process by converging two parallel lines of research, one centered on sensorimotor timing, and the other on cognitive mapping in the hippocampal system. By combining functional magnetic resonance imaging (fMRI) with a fastpaced time-to-contact (TTC) estimation task, we found that the hippocampus signaled behavioral feedback received in each trial as well as performance improvements across trials along with reward-processing regions. Critically, it signaled performance improvements independent from the tested intervals, and its activity accounted for the trial-wise regression-to-the-mean biases in TTC estimation. This suggests that the hippocampus supports the rapid encoding of temporal context even on short time scales in a behavior-dependent manner. Our results emphasize the central role of the hippocampus in statistical learning and position it at the core of a brain-wide network updating sensorimotor representations in real time for flexible behavior.
Growth and nutritional status of maize plants in response to different doses and application frequencies of biofertilizer

This study analyzed the effect of different doses and application frequencies of a dairy cattle-derived biofertilizer on the growth and nutritional status of maize cv. BRS Caatingueiro in a Yellow Latosol. The experiment was con­ducted in an open-air nursery at the Federal University of Vale do Sao Francisco, Juazeiro-BA. The experimental design was a randomized complete block design in a 6 x 2 factorial scheme, with six biofertilizer doses (0, 120, 240, 360, 480, and 600 mL per plant) and two fertigation frequencies (7 and 14 days), with five replicates. The seeds of maize cv. BRS Caatingueiro were planted in pots filled with Yellow Latosol. During the crop cycle (90 days), the following variables were evaluated: height, diameter, and number of leaves. During harvest, the varia­bles evaluated were: root and shoot fresh and dry weight, root volume, chlorophyll index, and macro- and micro­nutrient contents of leaf and root tissue. Biofertilizer applications at14-day frequencies promoted better plant growth compared to 7-day frequencies. However, despite the lower accumulation of some nutrients in relation to the application of larger doses, the dose of 360 mL biofertilizer promoted better root and leaf growth. Considering the uniformity and economy of the application of the product, it is recommended to apply the dose of 360 mL per plant every 14 days.
Active Learning in Computing: Engaging Learners in a Cross-Site Team Project

Active Learning in Computing (ALiC) is a CETL project led by the University of Durham, with the University of Newcastle, Leeds Metropolitan University and the University of Leeds as partners. The project focuses on increasing the level of student engagement within the Computing curriculum, aiming to make the student experience more relevant to industry. This paper concerns an experiment being undertaken jointly by the ALiC researchers at Newcastle and Durham. The pedagogical aims are to increase engagement and simulate the working practices of large companies, specifically running software development projects with teams at different geographical locations. The experiment consists of an assignment shared between teams of second year students on the Software Engineering Modules at Durham and Newcastle, where regular communication helps achieve success. The teams can use communication methods such as email and face-to-face meetings onsite and email, SMS, bulletin boards and video-conferencing for contacting their offsite counterparts. The structure of the assignment gives an insight into Software Engineering in an industrial context, makes problem-solving more realistic and also encourages the development of transferable skills. The assessments allow students to reflect upon their individual and team performance and to explore the roles and skills required when working in teams. This paper reviews the Newcastle students' perceptions of their skill levels and choice of team structure at the beginning of the team project and compares them to their reports at the interim stage. It also outlines what the module leaders have learned so far and how they will refine the design of the assignment in the future.
Detection of Bacterial Isolation and Antimicrobial Resistance Profiles in Goat Mastitis

Mastitis is one of the most common infections worldwide. This infection poses risks to animal and public health. Therefore, determination of mastitis pathogens is important for the prevention of the infection. Generally, the combination of antimicrobials is an effective, reliable and common treatment approach. In this study, it was aimed to determine the bacterial mastitis pathogens in goat’s milk and antimicrobial resistance profiles of these pathogens. A total of 190 goat milk samples were examined with standard microbiological analysis in the period of 2018-2019. Bacterial mastitis pathogens were obtained in 33.2% of all samples. Totally, 79 different bacterial agents were isolated due to multiple-bacterial isolation. Major genus was detected as Staphylococcus spp. (66%): coagulase-negative Staphylococcus (CNS) 44% and coagulase-positive Staphylococcus (CPS) 22%. This group was followed by respectively Bacillus spp. (17.6%), catalase-negative cocci (PNC) (14%), Mannheimia spp. (1.2%) and Micrococcus spp. (1.2%). The most prevalent species were identified Staphylococcus caprae (27%), Staphylococcus aureus and Staphylococcus chromogenes (13%), Aerococcus viridans and Bacillus cereus (7.6%). Considering the antimicrobial resistance test, tetracycline has the highest resistance rate (31%) among the tested antimicrobials. A total of 4 multi-drug resistant isolates were found: an Enterococcus faecalis and three Streptococcus uberis isolates. The highest resistance rate (35.7%) was observed for penicillin in all Bacillus spp. isolates.
Understanding viscoelastic flow instabilities using the Oldroyd-B model

The Oldroyd-B model has been used extensively to predict a host of instabilities in shearing flows of viscoelastic fluids, polymer solutions in particular. The present review, written on the occasion of the birth centenary of James Oldroyd, provides an overview of the instabilities found in major classes of shearing flows. The latter consist of the canonical rectilinear shearing flows including plane Couette, plane Poiseuille and pipe Poiseuille flows, viscometric shearing flows with curved streamlines which include the Taylor-Couette, cone-and-plate and parallel-plate geometries, non-viscometric shearing flows with an underlying extensional flow topology, and multilayer shearing flows; the underlying focus in all these cases is on results obtained using the Oldroyd-B model, and their relation to the actual instability. All the three commonly used tools of stability analysis, viz., modal linear stability, nonmodal stability, and weakly nonlinear stability analyses are discussed, with supporting evidence from experiments and numerical simulations as appropriate. Despite only accounting for a shear-rate-independent viscosity and first normal stress coefficient, the Oldroyd-B model is able to qualitatively predict the majority of instabilities in the aforementioned shearing flows. The review also highlights, where appropriate, open questions in the area of viscoelastic stability.