Miracle-dz/UniFAR-FTUs huggingface dataset:
Digital learning ecologies and professional development of university professors

This study analyses the extent towhich university faculty use the technological resources thatmake up their LearningEcologies to promote their professional development as educators. The interest of this research lies on the growing impact of Learning Ecologies as a framework to examine the multiple learning opportunities provided by a complex digital landscape. Global data referred to the use of technological resources grouped in three dimensions (information access, search and management resources, creation and content editing resources, and interaction and communication resources) has been identified. In addition, the influence of different variables such as gender, age, years of teaching experience and the field of knowledgewere also examined. The study was conducted using a survey-based quantitative methodology. The sample consisted of 1,652 faculty belonging to 50 Spanish universities. To respond to the objectives of the study, descriptive and inferential analyses (ANOVA) were carried out. On the one hand, a moderate use of technological resources for professional development was noted while on the other hand, significant differences were observed on all variables analyzed. The results suggest a need to promote, both at the individual and institutional levels, more enriched Learning Ecologies, in such a way that each professor can harness the learning opportunities afforded by the networked society. RESUMEN En este estudio se analiza en qué medida el profesorado universitario utiliza los recursos tecnológicos que configuran sus Ecologías de Aprendizaje para propiciar su desarrollo profesional como docentes. El interés de esta investigación radica en el creciente impacto del constructo de las Ecologías de Aprendizaje como marco para examinar e interpretar las múltiples oportunidades de aprendizaje que ofrece el complejo panorama digital actual. Además de identificar los datos globales referidos al uso de los recursos tecnológicos agrupados en tres dimensiones (recursos de acceso, búsqueda y gestión de la información, recursos de creación y edición de contenido, y recursos de interacción y comunicación), también se examina la influencia de diferentes variables como el género, la edad, los años de experiencia docente y la rama de conocimiento. La metodología empleada ha sido de corte cuantitativo a través de encuesta. La muestra está compuesta por 1.652 profesores pertenecientes a 50 universidades españolas. Para dar respuesta al objetivo del estudio se llevaron a cabo análisis descriptivos e inferenciales (ANOVA). Se constata un empleo moderado de los recursos tecnológicos para el desarrollo profesional y, además, se observan diferencias significativas en función de las variables analizadas. Los resultados alertan de la necesidad de fomentar, tanto a nivel individual como institucional, Ecologías de Aprendizaje más enriquecidas, de manera que cada docente pueda aprovechar mejor las posibilidades de aprendizaje que ofrece la sociedad en red.
Routing and Neighbor Node Cooperation Scheme to Achieve Energy Efficient Encryption for Integrating Wireless Sensor Networks with Internet

The integration of Wireless Sensor Networks (WSNs) with IP network has created IP specific security issues which were absent in classical WSNs. Most of the security issues in the IP network such as: data packet encryption, are addressed through computationally expensive security mechanisms. Recently, WSN data packet encryption scheme through 3 Data Encryption Standard (3DES) technique was presented in the literature. However, the 3DES technique, even-though provides robust security merits in data packet encryption, requires significant computational investment. It must be noted that, the sensor nodes depend upon limited energy reserves, and large computational load can rapidly deplete the energy reserves. Hence, the main open issue is to utilize 3DES encryption technique by incurring limited energy expenditures for WSNs. To achieve this open issue, an energy efficient encryption scheme denoted as Routing and Neighbor Node Cooperation (RNNC) is presented in this paper. The salient features of RNNC scheme are: it utilizes 3DES technique for data packet encryption; it distributes the encryption load of the source node to the neighbor and routing nodes; it achieves node energy conservation by distributing the encryption load, and still retains the security benefits of 3DES technique. The RNNC scheme is designed through randomized algorithm. Simulation study details of RNNC scheme against the contemporary technique are presented. In this simulation study, the RNNC scheme provides significant energy conservation benefits WRT data packet encryption against the contemporary technique.
A Subspace Method for Blind Channel Estimation in CP-free OFDM Systems

In this paper, a subspace method is proposed for blind channel estimation in orthogonal frequency-division multiplexing (OFDM) systems over time-dispersive channel. The proposed method does not require a cyclic prefix (CP) and thus leading to higher spectral efficiency. By exploiting the block Toeplitz structure of the channel matrix, the proposed blind estimation method performs satisfactorily with very few received OFDM blocks. Numerical simulations demonstrate the superior performance of the proposed algorithm over methods reported earlier in the literature.
Computational studies of the bulk cobalt pentlandite (Co9S8): Validation of the potential model

We use the density functional theory to study the cobalt pentlandite mineral, (Co9S8). We investigate various forms of the cobalt pentlandite, Co9S8, at different temperatures, using classical atomistic simulation methods with the support of electronic structure calculations. The first interatomic potentials of Co9S8 based on the Born model, were derived with input data such as structure and elastic properties from experiments and electronic structure calculations respectively. The interatomic potentials were validated by running energy minimization and molecular dynamics calculations. The structure and elastic properties corresponded well with those determined by electronic structure methods. The calculations further reproduced the complex high temperature transformation to high form pentlandite and the melting of Co9S8; as deduced from the crystal structure and radial distribution functions.
Tuina Massage Improves Cognitive Functions of Hypoxic-Ischemic Neonatal Rats by Regulating Genome-Wide DNA Hydroxymethylation Levels

In addition to abnormalities of motor and posture, children with cerebral palsy (CP) often have intellectual disability. As a complementary and alternative traditional Chinese medicine (TCM) therapy, Chinese Tuina massage, also called Tuina in China, has been widely applied in clinical treatment for CP in China for a long time. However, the molecular basis for this still remains largely unknown. Recently, DNA hydroxymethylation has been shown to be sensitive to environment and plays critical roles in some neurological disorders, whereas the research focusing on the relationship between 5 hmC and Tuina therapy for cerebral palsy is deficient. In our study, we first observed that Tuina improved learning and memory functions of hypoxic-ischemic (HI) rat pups. Meanwhile, 5 hmC level of the temporal lobe cortex in the HI neonatal rat model is decreased significantly compared to that of the rats in control and Tuina groups. Then, we used the hMeDIP-Seq method to explore whether and how DNA hydroxymethylation is involved in Tuina therapy for cerebral palsy. Genomic annotation of DhMRs of HI group's hypo-hydroxymethylation to genes revealed enrichment in multiple neurodevelopmental signaling pathways. Moreover, we found the depletion of 5 hmC modifications in genes associated with neuronal development was accompanied by reduced mRNA levels of these genes. Taken together, our results indicate that Tuina may regulate the expression of neurodevelopment-related genes by changing the status of DNA hydroxymethylation, thereby improving learning and memory functions of cerebral palsy.
Detection of Circulating Tumor Cell Molecular Subtype in Pulmonary Vein Predicting Prognosis of Stage I–III Non-small Cell Lung Cancer Patients

Background: There was rare studies on prognosis of pulmonary venous CTC and early or advanced NSCLC patients. We want to investigate whether CTCs and the subtype of it can predict the prognosis of NSCLC patients. Patients and Methods: One hundred and fourteen patients with stage I-III NSCLC were included CanPatrol™ CTC analysis. PD-L1 expression level were detected in CTC of pulmonary vein. PD-L1, number of CTC in pulmonary, CTC's subtype, clinical characteristics, prognosis of patients were analyzed. Results: 110/114 (96.5%) patients could be found CTCs in pulmonary vein, 58/114 (50.9%) patients had CTC≥15/ml in pulmonary vein, 53/110 patients (48.2%) were defined as having MCTC subtype and 56/110 patient were found have PD-L1 (+) CTC in pulmonary vein. Multivariate analyses showed that PVCTC, MCTC, and stage were independent factors of DFS (P < 0.05). No OS difference was found between number of CTC (P = 0.33) and other CTC factors (P > 0.05), only stage was independent factor of OS (P = 0.019). There were decreases of CTC number and MCTC number in EGFR mutant subgroup (P = 0.0009 and P = 0.007). There were increases of CTC (P = 0.0217), MCTC (P = 0.0041), and PD-L1 (+) CTC (P = 0.0002) number in KRAS mutant subgroup. There was increase of MCTC (P =0.0323) number in BRAF mutant. There were fewer CTCs in pulmonary vein for patients with EGFR mutant than in patients with full wild-type gene (P = 0.0346). There were more PD-L1 positive CTCs in pulmonary vein for patients with ALK rearrangement, KRAS mutant, BRAF mutant, or ROS1 mutant than in patients with full wild-type gene (P = 0.0610, P = 0.0003, P = 0.032, and P = 0.0237). There were more mesenchymal CTCs in pulmonary vein for patients with KRAS mutant and BRAF mutant than in patients with full wild-type gene (P = 0.073 and P = 0.0381). There were fewer mesenchymal CTCs in pulmonary vein for patients with EGFR mutant than in patients with full wild-type gene (P = 0.0898). Conclusions: The patients with high number of CTCs, MCTCs, or PD-L1 (+) CTCs in pulmonary vein experienced poor prognosis of DFS. There are obvious correlations between the CTC subtype of NSCLC and the gene subgroups of tumor tissue.
Divergent Patterns of Carbon, Nitrogen, and Phosphorus Mobilization in Forest Soils

Carbon (C), nitrogen (N), and phosphorus (P) become released in inorganic or organic forms during decomposition of soil organic matter (SOM), often at varying rates. Our study aimed at identifying the individual patterns and controls of C, N, and P mobilization in soils under beech forests. We exposed organic and mineral horizons sampled along a nutrient availability gradient in Germany to either permanent moist conditions or to dry spells in microcosms and quantified the release of inorganic and organic C, N, and P. In the moist control treatment, releases of DOC, DON and DOP were interrelated and depended on the C:N:P ratio of SOM, whilst net mineralization rates of C, N and P were poorly correlated. Mineralization of C decreased with soil depth from Oi to A horizons, reflecting the increasing SOM stability. Net mineralization of N and P showed divergent depth patterns. In the Oi horizon, microbial immobilization was more pronounced for N than for P. In A horizons, net mineralization of P was less than of N, very likely because of strong sorption of released phosphate by mineral phases. Counterintuitively, net P mineralization in A horizons increased towards P-poor sites, probably due to decreasing contents of clay and pedogenic oxides, and thus, declining P sorption. Drying and rewetting caused stronger mobilization of inorganic and organic P, and organic N than of inorganic C and inorganic N, most likely by lysis of microbial biomass with tight C:N:P ratios. Due to the divergent patterns in N and P cycling, the organic layer is more important for the mineralization of P than the mineral soil; for N the mineral soil is most relevant. Consequently, the loss of the organic layer would deteriorate P nutrition, in particular at nutrient-poor sites. Overall, our results indicate that the cycling of C, N, and P is not directly coupled due to the different microbial processing and, in the mineral soil, differential sorption of N and P. This may ultimately cause imbalances in the N and P nutrition of forests.
Analyzing Player Engagement for Biofeedback Games

Stress is currently one of society’s dominant health problems with far-reaching effects on human health. Traditional methods of stress therapy are expensive and have low adherence levels. There is growing research in the area of biofeedback (BF) games, in order to provide cheaper and more engaging alternatives. In our previous work, we presented three BF games, and showed how these games helped manage stress better than traditional stress therapy activities, like Paced Breathing. Given the crucial role engagement can play in determining the effectiveness of learning stress self-regulation in our biofeedback games, in this paper we investigate how best to quantify engagement physiologically. To achieve this, we pursue two main goals: 1) provide a framework for evaluating player engagement, and 2) develop machine learning models to predict levels of engagement during these stress therapy activities. Our main contributions are to present a metric for engagement based on physiological profiles, provide a benchmark for engagement levels and present a combination of evaluation criteria to determine if a BF game session was Highly Engaged (HE) or Poorly Engaged (PE). Additionally, for each evaluation criterion, we build a Support Vector Machine (SVM) to predict if the BF game session can be labelled as HE or PE. Our work, especially relating to levels of engagement, can easily be generalized to analyzing other physiological profiles using breathing rate and Heart Rate Variability (HRV).
Heterocycles in Medicinal Chemistry

Heteroatoms constitute a very common fragment of a number of active pharmaceutical ingredients as well as excipients; from the point of view of significance, it is all the same if these are isosterically/bioisosterically replaced carbons/carbon substructures in aliphatic structures or real heterocycles [. ].
Prediction of Negative Conversion Days of Childhood Nephrotic Syndrome Based on PCA and BP-AdaBoost Neural Network

The prognosis of childhood nephrotic syndrome directly hinges on the accurate prediction of negative conversion days (NCDs). Therefore, this paper designs a hybrid approach of principal component analysis (PCA) and backpropagation (BP)-adaptive boosting (AdaBoost) neural network (NN), and applies the method to predict the NCDs for children with nephrotic syndrome. Specifically, PCA method was employed for dimension reduction. Six principal components were extracted from multiple physiological features, and taken as input variables of three-tiered neural networks. The boosted predictor of BP-AdaBoost model, together with three predictors of BP NN, support vector machine (SVM) and radial basis function (RBF) NN, was trained for NCDs prediction. The experimental results show that the predictor of BP-AdaBoost NN achieves the mean absolute error of 0.2334, the mean relative error of 3.2789%, the SD of 4.6804 and the RSD of 50.8053% in NCDs prediction, and it outperforms other predictors of BP NN, SVM and RBF NN on both accuracy and precision. Furthermore, comparison experiments are conducted on PCA processed testing data and raw testing data for BP-AdaBoost NN and demonstrate the excellent effect of PCA. The hybrid approach of PCA and BP-AdaBoost NN is simple and reliable for NCDs prediction of childhood nephrotic syndrome, and it can help pediatricians prognose childhood nephrotic syndrome accurately and further provide patients with better care and treatment.
Detecting Bottleneck and Fraud in Agile Development by using Petri net Performance and Trace Clustering

Software Development Life Cycle model is one of the basic idea of the software development. SDLC is a continuous process, the cycle starts from the moment when it is decide to release the project, and it ends when its full remove from the exploitation. Agile is one of the mostly used SDLC models. Combination of incremental and iterative process models with a focus on process customer satisfaction and can adapt to rapid delivery of working sofware is called Agile SDLC. This contribution of this paper is evaluating the performance, such as occurring bottleneck and fraud, of an Agile model to handle the management of the project. This paper uses Petri net to analyze Agile SDLC model performance. The petri net use to detect the bottleneck that occur in the model. If an event has longer waiting time tahen others, it can identify that the bottleneck occur in that task. Then, the fraud is detected based on trace clustering. Based on the experiment, the cluster which has lowest member is indicates as fraud processes.
A Privacy Protection Scheme of Microgrid Direct Electricity Transaction Based on Consortium Blockchain and Continuous Double Auction

Low cost, high efficiency, price transparency, and timely settlement of transactions are required for direct transactions between electricity providers and consumers in the microgrids. So the blockchain technology and the continuous double auction mechanism for direct electricity trading have always been a hot topic in the field of microgrids.In order to further reduce the transaction cost of blockchain and increase the transaction efficiency, and to solve the problem of lack of privacy protection for continuous double auction in the existing scheme, a privacy protection scheme of microgrids direct electricity transaction based on consortium blockchain and the continuous double auction is proposed. In it, the combination of consortium blockchain technology and continuous double auction mechanism is applied to reduce costs and improve the efficiency of transactions. In the meanwhile, pseudonyms and pseudonym certificates are generated by fair blind signature technology to realize identity privacy in the continuous double auction. And decentralization and user identity traceability are achieved by using (t, n) threshold secret sharing technology which distributes and recovers the private key of a trusted third party. The theoretical security analysis shows that the privacy protection scheme has higher security. The simulation experiment shows that the consortium blockchain technology has lower cost and higher efficiency in this scheme.
Foundations and Evolution of Modern Computing Paradigms: Cloud, IoT, Edge, and Fog

In the last few years, Internet of Things, Cloud computing, Edge computing, and Fog computing have gained a lot of attention in both industry and academia. However, a clear and neat definition of these computing paradigms and their correlation is hard to find in the literature. This makes it difficult for researchers new to this area to get a concrete picture of these paradigms. This work tackles this deficiency, representing a helpful resource for those who will start next. First, we show the evolution of modern computing paradigms and related research interest. Then, we address each paradigm, neatly delineating its key points and its relation with the others. Thereafter, we extensively address Fog computing, remarking its outstanding role as the glue between IoT, Cloud, and Edge computing. In the end, we briefly present open challenges and future research directions for IoT, Cloud, Edge, and Fog computing.
NUMERICAL INVESTIGATION OF CLOSURES FOR INTERFACE FORCES IN DISPERSED FLOWS USING A 3D FRONT TRACKING MODEL

Closures for the drag, virtual mass and lift forces acting on a single air bubble or toluene droplet in water have been studied using a 3D Front Tracking model. The numerical implementation of the FT model was improved to allow simulations of very small air bubbles rising in water (~1 mm) using realistic physical properties. For this system the surface tension force, density ratio and the Reynolds number all are very high. The computed drag force coefficient for air bubbles in water (1-5 mm diameter) compare reasonably well with experimental data obtained results using ultra pure water. Similar drag coefficients were computed for toluene droplets rising in water, as expected since these two systems possess comparable Morton numbers. For the virtual mass coefficient a value of 0.53 was found on a 80x80x80 grid for air bubbles in water, which compares very well with the theoretical value of 0.50. Finally, the lift force coefficient was computed for a 4 mm air bubble rising in water. A value of 0.5 was computed, which is slightly higher than reported experimentally at somewhat lower Reynolds numbers.
Emerging Trends, Techniques and Open Issues of Containerization: A Review

Containerization is revolutionizing the way that many industries operate, provisioning major impact to modern computing technologies because it is extra lightweight, highly portable, energy, resource and storage efficient, cost-effective, performance efficient, and extremely quick during boot up. These often facilitate efficient load balancing, low-level system maintenance, server consolidation (for efficient energy and resource utilization) and replication of instances over geographical locations for better fault tolerance to escalate application reliability. However, some recent literature have addressed various challenges (such as <inline-formula> <tex-math notation="LaTeX">$complex$ </tex-math></inline-formula> networking, <inline-formula> <tex-math notation="LaTeX">$persistent~storage$ </tex-math></inline-formula> facilities, <inline-formula> <tex-math notation="LaTeX">$cross~data$ </tex-math></inline-formula> centers and <inline-formula> <tex-math notation="LaTeX">$multicloud$ </tex-math></inline-formula> supports, <inline-formula> <tex-math notation="LaTeX">$security$ </tex-math></inline-formula> issues, and <inline-formula> <tex-math notation="LaTeX">$lack$ </tex-math></inline-formula> of available, capable container management <monospace>API</monospace>s, etc.) regarding successful container adoption in industries, which might have resulted in a seemingly meager increase in industrial deployments of containerization over the past few years despite bestowing efficient lightweight virtualization. Moreover, a comprehensive overview of containerizations along with their popularity dynamics has still not been found in contemporary literature, which further extends knowledge gap between developers and available technologies. Hence, current study touches upon different technicalities involved in containerization with potential problems and possible solutions along with various important industrial applications to manifest its existing supports and technical hardships. Finally, we have conducted a comprehensive experimental study to compare the performance of <monospace>VM</monospace>s, containers and unikernels in terms of <monospace>CPU</monospace> utilization, memory footprints, network bandwidth, execution time and technological maturity using standard benchmarks and observed containers to deliver satisfactory performance in almost all aspects, however, are still not free from issues regarding isolation & security, performance stability, lack of available efficient tools for cross-platform support and persistent storage. Unikernels deliver good performance with <monospace>VM</monospace>-like isolation but still need to achieve desired technical maturity (in terms of microprocessor stability, process containment, persistent storage, etc.). <monospace>VM</monospace>s, on the other hand, are found to provide stable performance throughout, though bigger memory footprints and slower spin up/down remain their biggest weaknesses.