Peer evaluation system: a web application to provide peer evaluation for a workshop

Treballs Finals de Grau d'Enginyeria Informàtica, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2022, Director: Eloi Puertas i Prats[en] For any academic organization, the link between student and professor is the main support on which academic knowledge is based. Students are the ones who take a set of subjects and will be evaluated along the course. In contrast, professors are the ones who will evaluate the students by a set of criteria for each assignment of the subject. This evaluation procedure is known as the standard way to provide a qualification to the student where the professor is the only one who can influence the qualification. This project is focused on the workflow of the whole evaluation period of an activity where students not only participate in the task but also evaluate their peers to get scored after the task is finished. Its goal is to analyze the current workshop activity on the virtual campus of the University of Barcelona (based on Moodle) and then synthesize the core requirements of the system into the designed web application that serves as a third-party platform that is more intuitive for both students and professors to get into. By this, a whole sequence of the evaluation will take place at a web application which is the platform where students can participate in the process of peer evaluation in the same task. While the professor is responsible for evaluating both the evaluations given by the students and the attached files

A Novel Interface Database of Graphene Nanoribbon from Density Functional Theory

Interfaces play a crucial role in determining the overall performance and functionality of electronic devices and systems. Driven by the data science, machine learning (ML) reveals excellent guidance for material selection and device design, in which an advanced database is crucial for training models with state-of-the-art (SOTA) precision. However, a systematic database of interfaces is still in its infancy due to the difficulties in collecting raw data in experiment and the expensive first-principles computational cost in density functional theory (DFT). In this paper, we construct ample interface structures of graphene nanoribbons (GNR), whose interfacial morphology can be precisely fabricated based on specific molecular precursors. The GNR interfaces serve as promising candidates since their bandgaps can be modulated. Their physical properties including energy bands and density of states (DOS) maps are obtained under reasonable calculation parameters. This database can provide theoretical guidance for the design of electronic devices and accelerate the ML study of various physical quantities

Phosphorus-doped porous carbons as efficient electrocatalysts for oxygen reduction

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.Efficient electrocatalysts for the oxygen reduction reaction (ORR) play a critical role in the performance of fuel cells and metal–air batteries. In this study, we report a facile synthesis of phosphorus (P)-doped porous carbon as a highly active electrocatalyst for the ORR. Phosphorus-doped porous carbon was prepared by simultaneous doping and activation of carbon with phosphoric acid (H3PO4) in the presence of Co. Both phosphorus and cobalt were found to play significant roles in improving the catalytic activity of carbon for the ORR. The as-prepared phosphorus-doped porous carbon exhibited considerable catalytic activity for the ORR as evidenced by rotating ring-disk electrode studies. At the same mass loading, the Tafel slope of phosphorus-doped porous carbon electrocatalysts is comparable to that of the commercial Pt/C catalysts (20 wt% Pt on Vulcan XC-72, Johnson Matthey) with stability superior to Pt/C in alkaline solutions

A fully-mapped and energy-efficient FPGA accelerator for dual-function AI-based analysis of ECG

In this paper, a fully-mapped field programmable gate array (FPGA) accelerator is proposed for artificial intelligence (AI)-based analysis of electrocardiogram (ECG). It consists of a fully-mapped 1-D convolutional neural network (CNN) and a fully-mapped heart rate estimator, which constitute a complementary dual-function analysis. The fully-mapped design projects each layer of the 1-D CNN to a hardware module on an Intel Cyclone V FPGA, and a virtual flatten layer is proposed to effectively bridge the feature extraction layers and fully-connected layer. Also, the fully-mapped design maximizes computational parallelism to accelerate CNN inference. For the fully-mapped heart rate estimator, it performs pipelined transformations, self-adaptive threshold calculation, and heartbeat count on the FPGA, without multiplexed usage of hardware resources. Furthermore, heart rate calculation is elaborately analyzed and optimized to remove division and acceleration, resulting in an efficient method suitable for hardware implementation. According to our experiments on 1-D CNN, the accelerator can achieve 43.08× and 8.38× speedup compared with the software implementations on ARM-Cortex A53 quad-core processor and Intel Core i7-8700 CPU, respectively. For the heart rate estimator, the hardware implementations are 25.48× and 1.55× faster than the software implementations on the two aforementioned platforms. Surprisingly, the accelerator achieves an energy efficiency of 63.48 GOPS/W, which obviously surpasses existing studies. Considering its power consumption is only 67.74 mW, it may be more suitable for resource-limited applications, such as wearable and portable devices for ECG monitoring

PSR J1926-0652: A Pulsar with Interesting Emission Properties Discovered at FAST

We describe PSR J1926-0652, a pulsar recently discovered with the Five-hundred-meter Aperture Spherical radio Telescope (FAST). Using sensitive single-pulse detections from FAST and long-term timing observations from the Parkes 64-m radio telescope, we probed phenomena on both long and short time scales. The FAST observations covered a wide frequency range from 270 to 800 MHz, enabling individual pulses to be studied in detail. The pulsar exhibits at least four profile components, short-term nulling lasting from 4 to 450 pulses, complex subpulse drifting behaviours and intermittency on scales of tens of minutes. While the average band spacing P3 is relatively constant across different bursts and components, significant variations in the separation of adjacent bands are seen, especially near the beginning and end of a burst. Band shapes and slopes are quite variable, especially for the trailing components and for the shorter bursts. We show that for each burst the last detectable pulse prior to emission ceasing has different properties compared to other pulses. These complexities pose challenges for the classic carousel-type models.Comment: 13pages with 12 figure

Use of MicroRNA Let-7 to Control the Replication Specificity of Oncolytic Adenovirus in Hepatocellular Carcinoma Cells

Highly selective therapy for hepatocellular carcinoma (HCC) remains an unmet medical need. In present study, we found that the tumor suppressor microRNA, let-7 was significantly downregulated in a proportion of primary HCC tissues (12 of 33, 36.4%) and HCC cell lines. In line with this finding, we have engineered a chimeric Ad5/11 fiber oncolytic adenovirus, SG7011let7T, by introducing eight copies of let-7 target sites (let7T) into the 3′ untranslated region of E1A, a key gene associated with adenoviral replication. The results showed that the E1A expression (both RNA and protein levels) of the SG7011let7T was tightly regulated according to the endogenous expression level of the let-7. As contrasted with the wild-type adenovirus and the control virus, the replication of SG7011let7T was distinctly inhibited in normal liver cells lines (i.e. L-02 and WRL-68) expressing high level of let-7 (>300 folds), whereas was almost not impaired in HCC cells (i.e. Hep3B and PLC/PRF/5) with low level of let-7. Consequently, the cytotoxicity of SG7011let7T to normal liver cells was successfully decreased while was almost not attenuated in HCC cells in vitro. The antitumor ability of SG7011let7T in vivo was maintained in mice with Hep3B xenograft tumor, whereas was greatly decreased against the SMMC-7721 xenograft tumor expressing a high level of let-7 similar with L-02 when compared to the wild-type adenovirus. These results suggested that SG7011let7T may be a promising anticancer agent or vector to mediate the expression of therapeutic gene, broadly applicable in the treatment for HCC and other cancers where the let-7 gene is downregulated