Miracle-dz/UniFAR-FTUs huggingface dataset:
Current and Future Role of Medical Imaging in Guiding the Management of Patients With Relapsed and Refractory Non-Hodgkin Lymphoma Treated With CAR T-Cell Therapy

Chimeric antigen receptor (CAR) T-cells are a novel immunotherapy available for patients with refractory/relapsed non-Hodgkin lymphoma. In this indication, clinical trials have demonstrated that CAR T-cells achieve high rates of response, complete response, and long-term response (up to 80%, 60%, and 40%, respectively). Nonetheless, the majority of patients ultimately relapsed. This review provides an overview about the current and future role of medical imaging in guiding the management of non-Hodgkin lymphoma patients treated with CAR T-cells. It discusses the value of predictive and prognostic biomarkers to better stratify the risk of relapse, and provide a patient-tailored therapeutic strategy. At baseline, high tumor volume (assessed on CT-scan or on [18F]-FDG PET/CT) is a prognostic factor associated with treatment failure. Response assessment has not been studied extensively yet. Available data suggests that current response assessment developed on CT-scan or on [18F]-FDG PET/CT for cytotoxic systemic therapies remains relevant to estimate lymphoma response to CAR T-cell therapy. Nonetheless, atypical patterns of response and progression have been observed and should be further analyzed. The potential advantages as well as limitations of artificial intelligence and radiomics as tools providing high throughput quantitative imaging features is described.
Immune Checkpoint Inhibitor-Associated Pneumonitis in Non-Small Cell Lung Cancer: Current Understanding in Characteristics, Diagnosis, and Management

Immunotherapy that includes programmed cell death-1 (PD-1), programmed cell death- ligand 1 (PD-L1) and cytotoxic T lymphocyte antigen 4 (CTLA-4) inhibitors has revolutionized the therapeutic strategy in multiple malignancies. Although it has achieved significant breakthrough in advanced non-small cell lung cancer patients, immune-related adverse events (irAEs) including checkpoint inhibitor pneumonitis (CIP), are widely reported. As the particularly worrisome and potentially lethal form of irAEs, CIP should be attached more importance. Especially in non-small cell lung cancer (NSCLC) patients, the features of CIP may be more complicated on account of the overlapping respiratory signs compromised by primary tumor following immunotherapy. Herein, we included the previous relevant reports and comprehensively summarized the characteristics, diagnosis, and management of CIP. We also discussed the future direction of optimal steroid therapeutic schedule for patients with CIP in NSCLC based on the current evidence.
Deconvoluting the T Cell Response to SARS-CoV-2: Specificity Versus Chance and Cognate Cross-Reactivity

SARS-CoV-2 infection takes a mild or clinically inapparent course in the majority of humans who contract this virus. After such individuals have cleared the virus, only the detection of SARS-CoV-2-specific immunological memory can reveal the exposure, and hopefully the establishment of immune protection. With most viral infections, the presence of specific serum antibodies has provided a reliable biomarker for the exposure to the virus of interest. SARS-CoV-2 infection, however, does not reliably induce a durable antibody response, especially in sub-clinically infected individuals. Consequently, it is plausible for a recently infected individual to yield a false negative result within only a few months after exposure. Immunodiagnostic attention has therefore shifted to studies of specific T cell memory to SARS-CoV-2. Most reports published so far agree that a T cell response is engaged during SARS-CoV-2 infection, but they also state that in 20-81% of SARS-CoV-2-unexposed individuals, T cells respond to SARS-CoV-2 antigens (mega peptide pools), allegedly due to T cell cross-reactivity with Common Cold coronaviruses (CCC), or other antigens. Here we show that, by introducing irrelevant mega peptide pools as negative controls to account for chance cross-reactivity, and by establishing the antigen dose-response characteristic of the T cells, one can clearly discern between cognate T cell memory induced by SARS-CoV-2 infection vs. cross-reactive T cell responses in individuals who have not been infected with SARS-CoV-2.
The indirect effect of mRNA-based Covid-19 vaccination on unvaccinated household members

Abstract: This paper studies the direct and indirect effectiveness of Covid-19 vaccines among vaccinated healthcare workers and their unvaccinated adult household members in a mass vaccine program in Finland. Methods: We used national databases that record all polymerase chain reaction (PCR)-confirmed SARS-CoV-2 infections and mRNA-based (BNT162b2 by Pfizer-BioNTech or mRNA-1273 by Moderna) vaccine doses administered in Finland since the beginning of the epidemic. These data were merged with administrative full population datasets that include information on each person's occupation and unique identifiers for spouses living in the same household. To estimate the direct and indirect effectiveness of mRNA-based vaccines in a household setting, we compared the cumulative incidence of PCR-confirmed SARS-CoV-2 infections between vaccinated and unvaccinated healthcare workers as well as between their unvaccinated spouses. Findings: Our estimates imply indirect effectiveness of 8.7% (95% CI: -28.9 to 35.4) two weeks and 42.9% (95% CI: 22.3 to 58.1) 10 weeks after the first dose. The effectiveness estimates for unvaccinated household members are substantial, but smaller than the direct effect and occur more gradually among unvaccinated household members than among vaccinated individuals. Interpretation: Our results suggest that mRNA-based vaccines do not only prevent SARS-CoV-2 infections among vaccinated individuals but lead to a substantial reduction in infections among unvaccinated household members. The results are consistent with the notion that mRNA-based vaccines affect susceptibility in vaccinated individuals and prevent transmission from vaccinated to unvaccinated individuals.
Simultaneous determination of theanine,catechins and alkaloids in tea by HPLC-PDA

One method which could simultaneously determine the main components in tea,such as C,EC,EGC,ECG,EGCG,GCG,caffeine,theobromine,theophylline,theanine and gallic acid,was built by using HPLC-PDA.The method performed with a C18 chromatogram column and gradient elution at column temperature 25℃ and PDA detector at 190 nm and 280 nm.Mobile phase A was 0.05% trifluoroacetic acid and mobile phase B was acetonitrile.The flow rate was 1mL·min-1 and injection volume was 5 μL. The results showed that the calibration curves between peak areas and contents of components in tea were linear within the suitable concentration range.R2 was between 0.9989 and 0.9997,the mean recovery rates were from 96.31% to 103.13%. It is proved that this method is convenient and precise,which could be used for determination of catechins,theanine and alkaloids in tea and tea extracts.
Raising Awareness of Students' Self-Directed Learning Readiness (SDLR)

This paper describes the mapping of self-directed learning readiness (SDLR) for adult students applying for a master’s degree program delivered entirely as distanced learning. Since SDLR is strongly linked to both adult learning and online education, developing of self-directed learning (SDL) skills should be taken into consideration in our degree program. Making future students aware of SDLR is the first stage in introducing self-directed learning methods and practices in learning environments. The easiest way to do this is to have students answer an SDLR self-assessment questionnaire and give them feedback regarding their SDLR level. This paper presents how this is realized and provides the preliminary results of the study and the applicants’ SDLR score distributions. The results indicate high SDLR among all applicants.
Manipulatives for Teaching Introductory Programming to Struggling Students: A Case of Nested-decisions

Programming is one of the major subjects within the field of computing. In the higher education sector, some introductory programming students succeed while others find it difficult to progress or learn the material. Methods of teaching to program do not accommodate struggling students. Among introductory programming issues, the nested-decision statement is one of the misconceived concepts. In the literature, there is evidence that some programming educators make use of physical manipulatives to teach introductory programming. However, there is no framework or validation methods used to identify and use the manipulatives. In this study, we designed a manipulative called Nested-decider to assist struggling introductory programming students to develop an appropriate conceptual knowledge about nested-decisions. The details of the design and its functionalities are presented in this paper. We believe that teaching and learning nested-decisions with the proposed Nested-decider manipulative could be a useful pedagogical intervention towards enhancing struggling students’ comprehension. This is ongoing research where we identify and test various manipulatives for struggling introductory programming students. The results will also help us to develop a manipulatives – oriented pedagogical framework, which can be used to inform identification and use of
Supporting Automated Verification of Reconfigurable Systems with Product Lines and Model Checking

The capability to dynamically reconfigure in response to change of mode or function, failures, or unanticipated hazardous conditions is fundamental for many critical systems. The modelling and verification of such systems are frequently carried out with product lines and model checking, respectively. At first, the objectives and related requirements of reconfigurable systems are mapped to a feature model, whereas the units related to operational modes are selected in individual configurations. After that, the proposed approach performs automated transformation of particular models into formal constraints and descriptions for leveraging the analytical powers of model checking techniques; the formal verification of completeness, consistency and conflict is carried out with NuSMV model checker. Finally, in circumstances when the counterexample is produced, its analysis is performed for the identification of corresponding problems and their resolutions. The applicability of the proposed approach is demonstrated through case study of attitude and orbit control system.
A Neural Network Modelling and Prediction of Students' Progression in Learning: A Hybrid Pedagogic Method

The COVID-19 pandemic has changed dramatically the way how universities ensure the continuous and sustainable way of educating students. This paper presents the neural network (NN) modelling and predicting students’ progression in learning through a hybrid pedagogic method. The hybrid pedagogic approach is based on the revised Bloom’s taxonomy in combination with the flipped classroom, asynchronous and cognitive learning approach. To evaluate the effectiveness of the hybrid pedagogic approach and the students’ progression in learning, educational data is collected that comprises of labs and class test scores, as well as students’ total engagement and attendance metrics for the programming module considered. Conventional statistical evaluations are performed to evaluate students’ progression in learning. The NN is further modelled with six input variables, two layers of hidden neurons, and one output layer. Levenberg-Marquardt algorithm is employed as the back propagation training rule. The performance of neural network model is evaluated through the error performance, regression and error histogram. The NN model has achieved a good prediction accuracy along with limitations. Overall, the NN model presents how the hybrid pedagogic method in this case has successfully quantified students’ progression in learning throughout the COVID-19 period. Copyright © 2021 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved
Training School Activities to Promote a Conscious Use of Social Media and Human Development According to the Ecological Systems Theory

The analysis of the scientific literature suggests interesting results both on the positive and negative consequences of the use of the internet and social media during human development, during the school age. Yet several studies underline the need to consider Internet as a life context, therefore mediated by environmental factors, that can influence human development. In this article we emphasize the importance of the "educability" of the Internet and social media environments following an ecological perspective. In this regard, according to Bronfenbrenner's ecological systems theory of human development, we argue that it is possible to educate the school microsystem through specific training activities and innovative tools that assist students in analysing the effects of Web content personalization, understanding the algorithms controlling the social media mechanisms, and realising how toxic content propagate on the Web.
Ride-hailing Emissions Modeling and Reduction through Ride Demand Prediction

Transportation is the largest contributor of greenhouse gas emissions in the United States. As Transportation Network Companies (TNCs), such as Uber and Lyft, grow in prevalence, it is imperative to quantify their emissions impact. We studied the case of Austin, Texas through its primary ride-hailing service RideAustin that has released data on 1.4+ million individual rides over an 11-month period. We estimated a total of 6014.95 metric tonnes of CO2 emissions from deadheading (when there are no passengers in freight) over the given time period. We clustered Austin into different zones and built an LSTM-based neural network for hourly ride demand forecasting on each zone through spatiotemporal features (weather, federal holidays, day of the week, and a look-back interval). Despite a large out-of-time validation window (7 months), our model outperforms the XGBoost-based baseline model by 34.86% and the next best comparable model in current literature by 15.3% in terms of MAE. In addition, we estimated a 10.624% reduction in total deadheading emissions for the same period given that the ride-hailing drivers on road are routed according to the proposed hourly ride demand forecasts.
Student Perception of Usability: A Metric for Evaluating the Benefit When Adapting e-Learning to the Needs of Students with Dyslexia

Usability is now widely recognised as a critical factor to the success of e-learning systems. A highly usable e-learning system increases students’ satisfaction and engagement, thereby enhancing learning performance. However, one challenge in e-learning is poor engagement arising from a “one-size-fits-all” approach that presents learning content and activities in the same way to all students. Each student has different characteristics and, therefore, the content should be sensitive to these differences. This study evaluated the students’ perceived level of usability of an e-learning system that matches content to reading skill levels of students with dyslexia. 41 students rated their perceived usability of an e-learning system using the System Usability Scale (SUS). Results indicated that when the e-learning system matches content to students’ skill level, students perceive greater usability than when the learning is not matched. There was also a moderate, positive correlation between perceived usability and learning gain when e-learning was matched to their skill level. Thus, students assessment of the usability of a system is affected by the degree to which it is suited to their needs. This may be reflected in increased engagement and is associated with higher learning gain.
iTA: A Digital Teaching Assistant

Designed and implemented a question-answering chatbot, dubbed iTA (intelligent Teaching Assistant), which can provide detailed answers to questions by effectively identifying the most relevant answers in “long” text sources (documents or textbooks). iTA answers questions by implementing a two-stage procedure. First, the topmost relevant paragraphs are identified in the selected text source using a retrieval-based approach and scores for the retrieved paragraphs are computed. Second, using a generative model, extracted the relevant content from the top-ranked paragraph to generate the answer. Our results show that iTA is well suited to generate meaningful answers for questions posed by students.
Source Code based Approaches to Automate Marking in Programming Assignments

With the embarkment of this technological era, a significant demand over programming modules can be observed among university students in larger volume. When figures grow exponentially, manual assessments and evaluations would be a tedious and error-prone activity, thus marking automation has become fast growing necessity. To fulfil this objective, in this review paper, authors present literature on automated assessment of coding exercises, analyse the literature from four dimensions as Machine Learning approaches, Source Graph Generation, Domain Specific Languages, and Static Code Analysis. These approaches are reviewed on three main aspects: accuracy, efficiency, and user-experience. The paper finally describes a series of recommendations for standardizing the evaluation and benchmarking of marking automation tools for future researchers to obtain a strong empirical footing on the domain, thereby leading to further advancements
Supporting Educators to Design Collaborative Learning Scenarios

Collaborative learning (CL) processes are not always effective and the inadequate design of CL scenarios is one of the main causes of its unsuccess. Designing CL scenarios is a complex task, since it involves countless requirements and constraints that affect learning process and, hence, the learning outcomes. Consequently, CL scenarios are usually inappropriately structured. This study is particularly interested in the complexities inherent to the process of designing CL scenarios. Its objective is to propose a framework, composed of a conceptual metamodel and a computational tool, in order to support/guide educators throughout the process. The proposed framework was evaluated through a case study with 22 professors of a federal university. The results showed that with the framework it is possible to expose educators to design parameters in a way that they can effectively and systematically be specified.
Retrogradation—Digestibility Relationship of Selected Glutinous and Non-Glutinous Fresh and Stale Cooked Rice

This study examined the retrogradation and digestibility relationship of fresh and stale cooked rice of three rice varieties: glutinous (TDK11) and non-glutinous (Doongara and floating rice). The effect of rice variety, degree of milling and retrogradation (staling) of cooked rice on the estimated glycaemic index was determined. Although high-glycaemic index values were obtained for fresh cooked rice of all varieties, staling rice at 4oC for 24 h showed positive effect on floating rice only, yielding intermediate-glycaemic index. The effect of staling on retrogradation rates was corroborated by changes in x-ray diffraction peaks. The thermal and textural properties of rice samples showed higher pasting temperature, final viscosity, and hardness, and lower peak viscosity and adhesiveness for fresh cooked non-glutinous varieties, which were also significantly affected by degree of milling, in terms of hardness, after retrogradation.
Design and Validation of an Emerging Educational Technologies Acceptance and Integration Questionnaire for Teachers

The integration of technology in the teaching and learning processes depends to a large extent on the teaching attitude towards these resources. Thus, our research is focused on the internal beliefs that predisposed teachers to their acceptance and pedagogical use in schools. The main objective of this work was to design and validate a questionnaire for non-university teachers with the main purpose of identifying the most important factors of their teaching attitude towards the use of emerging technological resources. Taking the Theory of Planned Behaviour and its subsequent development as reference behavioural research models, we developed a questionnaire that interrelatedly combines the following factors: perceived usefulness, perceived self-efficacy, facilitating conditions and the subjective norm. A total of 661 teachers were recruited from public schools in La Rioja (Spain). Content validity, construct validity, internal consistency and reliability of the questionnaire were undertaken as part of the validation process. The results showed good psychometric qualities in the questionnaire and indicated that the instrument is reliable and a valid measure to identify the factors that explain the teaching attitude towards technological resources. The findings have both theoretical and practical implications for the educational administration, management teams and teachers.
Socio-demographic profile and mode of attempt of suicide among suicide attempters in Kashmir: a hospital-based study

Background: Suicide is an important and serious public health problem. It is one of the major emergencies in psychiatry. This study was carried out to assess the socio-demographic profile and mode of attempt of suicide among suicidal attempters attending emergency. Methods: This study was a cross sectional, observational study conducted at Institute of Mental Health and Neurosciences-Kashmir, an associated hospital of Government Medical College Srinagar, among the suicide patients attending the outpatient service and inpatient services fulfilling inclusion and exclusion criteria over a period of one and a half year. Each patient was informed about the purpose of interview; his/her consent was obtained in a simple and easily understandable unambiguous language. Results: A total of 221 cases who had been admitted following unsuccessful suicide attempts to the emergency and psychiatry department were taken up for the study. Out of which 161 (72.9%) were females and 60 (27.1%) were males, the mean age was 24.61±8.9 years. Lower middle and upper lower classes occupied an equal percentage of 34.4% of the suicide attempters, while 24% belonged to upper middle class and only 5.9% belonged to lower class . The least no. of cases (1.4%) were from the upper classes. The most common mode adopted was poisoning whereas the least common mode was selfimmolation. Poisoning and self-mutilation were proportionally high in females as compared to males with a significant p value. Conclusions: There should be a robust system in place which takes care of future management and follow up of this group of population.
Effect of Na on the structural and electrical properties of lead-free sodium potassium niobate ceramics

Abstract K1-xNaxNbO3 (where x = 0.48, 0.53, 0.56 and 0.60) (KNN) perovskite structured ferroelectric ceramics were prepared by the solid-state reaction method. X-ray diffraction patterns indicate that single orthorhombic phase was formed for KNN. Dielectric anomalies around 200°C and 370°C were identified as ferroelectric-ferroelectric and ferroelectric-paraelectric transition temperatures for KNN compound. The electrical behavior of KNN ceramics was studied by the help of impedance spectroscopy technique in the different temperature range. The impedance response in KNN ceramics could be resolved into a single contribution, associated with the bulk/grain. The conductivity studies confirm that the activation energies are strongly frequency dependent. A decreasing trend of Z′ with rise in temperature suggests the presence of negative temperature coefficient of resistance (NTCR) in the material in the low frequency region but tends to merge in the high frequency region at almost all temperatures.