Miracle-dz/UniFAR-FTUs huggingface dataset:
Generation of a pdmH1N1 2018 Influenza A Reporter Virus Carrying a mCherry Fluorescent Protein in the PA Segment

Influenza A virus (IAV) is a major human pathogen associated with significant morbidity and mortality worldwide. Through serial passage in mice, we generated a recombinant pdmH1N1 2009 IAV, A/Guangdong/GLW/2018 (GLW/18-MA), which encodes an mCherry gene fused to the C-terminal of a polymerase acidic (PA) segment and demonstrated comparable growth kinetics to the wild-type. Nine mutations were identified in the GLW/18-MA genome: PA (I61M, E351G, and G631S), NP (E292G), HA1 (T164I), HA2 (N117S and P160S), NA (W61R), and NEP (K44R). The recombinant IAV reporter expresses mCherry, a red fluorescent protein, at a high level and maintains its genetic integrity after five generations of serial passages in Madin-Darby Canine Kidney cells (MDCK) cells. Moreover, the imaging is noninvasive and permits the monitoring of infection in living mice. Treatment with oseltamivir or baicalin followed by infection with the reporter IAV led to a decrease in fluorescent protein signal in living mice. This result demonstrates that the IAV reporter virus is a powerful tool to study viral pathogenicity and transmission and to develop and evaluate novel anti-viral drugs, inhibitors, and vaccines in the future.
Biomechanical Characterization of Scallop Shells Exposed to Ocean Acidification and Warming

Increased carbon dioxide levels (CO2) in the atmosphere triggered a cascade of physical and chemical changes in the ocean surface. Marine organisms producing carbonate shells are regarded as vulnerable to these physical (warming), and chemical (acidification) changes occurring in the oceans. In the last decade, the aquaculture production of the bivalve scallop Argopecten purpuratus (AP) showed declined trends along the Chilean coast. These negative trends have been ascribed to ecophysiological and biomineralization constraints in shell carbonate production. This work experimentally characterizes the biomechanical response of AP scallop shells subjected to climate change scenarios (acidification and warming) via quasi-static tensile and bending tests. The experimental results indicate the adaptation of mechanical properties to hostile growth scenarios in terms of temperature and water acidification. In addition, the mechanical response of the AP subjected to control climate conditions was analyzed with finite element simulations including an anisotropic elastic constitutive model for a two-fold purpose: Firstly, to calibrate the material model parameters using the tensile test curves in two mutually perpendicular directions (representative of the mechanical behavior of the material). Secondly, to validate this characterization procedure in predicting the material’s behavior in two mechanical tests.
Driving Through a Bend: Detection of Unsafe Driving Patterns and Prevention of Heavy Good Vehicle Rollovers

Road Traffic Crashes are simply ordinary within the present world. However, heavy goods vehicles (HGV) rollover has become a significant problem worldwide. Depending on the data collected, the sources used, and several key factors contribute to HGV overturning. Accidents overturn due to longer reaction time, shriveled driving performance, lack of driving experience, and driver carelessness. In further consideration, over-steering to turning over, not steering enough to stay in lane, over speed, high located center of gravity, weather condition, road condition, and the road's curves are the most contributing reasons to the overturning of a long vehicle. Thus, this paper proposes machine learning processes to overcome these problems and reduce the HGV rollovers. The proposed system includes a vehicle-equipped system and a ground-based operational surveillance camera. The Vehicle-equipped system can determine the safe speed at which the vehicle should travel according to the type of vehicle and curvature of the road and can detect road cracks and notify the driver by sending the notification to the vehicle dashboard screen. The ground-based driver support system can detect safe speed for HGVs and determine various other traffic parameters which can affect the HGV rollover accidents.
High-Protein Concentrated Pro-Yogurt (Pro-WPI) Enriched With Whey Protein Isolate Improved Athletic Anemia and Performance in a Placebo-Controlled Study

Upcoming developments are attracting attention to both high-protein and probiotics supplementation for the sports community to promote good health and exercise performance. This study aimed at the production of high-protein concentrated pro-yogurt (Pro-WPI) enriched with 10 and 20% whey protein isolate (WPI) and investigation of the response of daily consumption on anthropometric, hematology parameters, and athletic performance in parallel with safety consideration assessment. Twenty-four athletes (19.6 ± 1.45 years; 175.96 ± 5.24 cm; 73.16 ± 8.65 kg) were participated in a randomized placebo-control study. They consumed Pro-WPI products with 10 (T1) and 20% (T2) WPI for treatments G1 (Pro-WPI30) and G2 (Pro-WPI60), respectively, 3 times per day/5 days per week/9 weeks. The taste of Pro-WPI products was sour and cheesy, while mouthfeel was described as soft and thick because of the increased protein content in T1 and T2 (14.15 and 22.58%). The hemoglobin of the athletes increased significantly from a baseline of 12.69 g/dl to 16 and 16.66 g/dl in G1 and G2, respectively. Furthermore, the athletic performance was enhanced in vertical jump, long jump, sprinting velocity, half squats, and pushups, which reached 58.75 cm, 255 cm, 3.5 m/s, 218.75 counts, and 85 counts, respectively in G2. The healthy gut microbiome (probiotics) in parallel with increased iron bioavailability by mineral binding (whey bioactive peptides), influenced iron status and can represent a healthy practice to improve athletic anemia and performance. On the other hand, urinary albumin exceeded the border of reference range (<30 mg/g) and reached 38.25 and 44.13 mg/g in G1 and G2, while urine pH was in the normal range (4.5–8). Increased urinary albumin might be due to high rates of protein metabolism that follow high protein intake. This study provided preliminary information on metabolic responses to high protein concentrated yogurt intake in athletes who engaged in daily exercise. Further studies are needed to determine the recommended intensity of 10 and 20% Pro-WPI product consumption to achieve its benefits and avoid implications on kidney function.
Optimization of Intention Detection Based on Metric Learning

With the development of machine learning, transfer learning has great development prospect and commercial value compared with the traditional supervised learning. As neural network developed, transfer learning based on metric learning is widely used in the field of Computer Vision and gradually applied to Natural Language Processing. This paper proposes to use BERT encoder and BiLSTM to improve the performance of intention detection especially in classification performance. SMP2017 data set shows that it can effectively improve the accuracy of intention detection when the sample size is small and uneven.
Generating Scenarios with Diverse Pedestrian Behaviors for Autonomous Vehicle Testing

: There exist several datasets for developing self-driving car methodologies. Manually collected datasets impose inherent limitations on the variability of test cases and it is particularly difﬁcult to acquire challenging scenarios, e.g. ones involving collisions with pedestrians. A way to alleviate this is to consider automatic generation of safety-critical scenarios for autonomous vehicle (AV) testing. Existing approaches for scenario generation use heuristic pedestrian behavior models. We instead propose a framework that can use state-of-the-art pedestrian motion models, which is achieved by reformulating the problem as learning where to place pedestrians such that the induced scenarios are collision prone for a given AV. Our pedestrian initial location model can be used in conjunction with any goal driven pedestrian model which makes it possible to challenge an AV with a wide range of pedestrian behaviors – this ensures that the AV can avoid collisions with any pedestrian it encounters. We show that it is possible to learn a collision seeking scenario generation model when both the pedestrian and AV are collision avoiding. The initial location model is conditioned on scene semantics and occlusions to ensure semantic and visual plausibility, which increases the realism of generated scenarios. Our model can be used to test any AV model given sufﬁcient constraints.
Evaluating the Usability of Mobile Applications: The Case of Covid-19 Apps in Saudi Arabia

Countries have used mobile applications (apps) creatively during the COVID-19 pandemic. In Saudi Arabia, the government has relied on several mobile apps to deal with different issues related to COVID-19, but so far there have not been enough studies conducted in the country to determine whether these mobile apps satisfy the principles of usability. This study takes a heuristic approach to evaluate and measure the usability of these apps. In particular, this study used SMART heuristics since they are designed specifically to evaluate usability on mobile devices and found that the apps Saudi Arabia has used during the pandemic suffer from several usability issues. We discuss these issues in detail and make recommendations to app designers in order to increase usability in their mobile apps.
Prevalence, Incidence, and External Causes of Traumatic Spinal Cord Injury in China: A Nationally Representative Cross-Sectional Survey

Background and Purpose The epidemiological characteristics of traumatic spinal cord injury (TSCI) in China are unclear. Thus, we aimed to study prevalence, incidence, and external causes of TSCI in China nationwide. Methods In 2013, we conducted a nationally representative, door-to-door epidemiological survey on TSCI in China using a complex, multistage, probability sampling design. Results In China, the point prevalence of TSCI standardized to the China census population 2010 was 569.7 (95% CI: 514.2–630.4) per 1,000,000 in the population, 753.6 (95% CI: 663.3–854.3) per 1,000,000 among men, and 387.7 (95% CI: 324.8–461.1) per 1,000,000 among women. The incidence of TSCI standardized to the China census population 2010 was 49.8 (95% CI: 34.4–70.7) per 1,000,000 per year in the population, 63.2 (95% CI: 38.9–98.5) per 1,000,000 among men, and 36.9 (95% CI: 19.5–65.9) per 1,000,000 among women. Among the 415 TSCI events in 394 prevalent cases, the top three injury causes were falls (55.2%), motor vehicle collisions (MVCs) (26.5%), and strike injuries (10.1%), while other injury causes including gunshot and explosion accounted for 8.2%. Among the 394 prevalent cases, the mean age of patients at the time of injury was 43.7 ± 17.1 years; the male-to-female ratio was 1.86:1. Conclusion It is estimated that there are 759,302 prevalent patients with TSCI in total and 66,374 new TSCI cases annually in China. Falls and MVCs are still 2 major external causes for TSCI in China.
Stabilized Controller for Jet Actuated Cantilevered Pipe Using Damping Effect of an Internal Flowing Fluid

Fluid jet actuation is a potential actuation technique for continuum robots. It can generate and rapidly control a relatively large force using a small and lightweight structure because a significant amount of energy can be transported through its internal channels. Recently, jet-actuated flying continuum robots have been developed using this advantageous characteristic. However, a challenging issue in controlling the robot is the fluid structure interaction between the flexible body and the internal flowing fluid. This interaction often causes instability in the pipe conveying fluid. In this study, as a first step to address this issue, we propose a stabilized controller (vertical position control) for a jet-actuated two-dimensional cantilevered pipe with a nozzle unit at the tip using the damping effect of the internal flowing fluid and verify the controller with a real robot. Specifically, a model is constructed with the net force of the jets as the control input. A simple controller that can constantly decrease the energy function is proposed by utilizing the damping effect of the flowing fluid. Numerical simulations verify the stability of the system regardless of the flow velocity. In particular, fluid damping mainly suppresses the higher-order mode oscillations. Moreover, the stability of the system can be improved by adjusting the controller gains. We also conduct experiments using an actual robot to verify the simulation results. The vibrations can be damped by the fluid effect, and the stability can be improved using the proposed controller.
Implementation of Synchronous Reference Frame theory for Harmonic Reduction in Computer Loads

This paper presents a non-linear control technique to reduce harmonic current in computer loads using active power filter. Nonlinear loads like personal computer draws non-sinusoidal current and produce distorted current waveform at three phase AC source. The usage of personal computers is increased today, that generates harmonics and creates severe problems in power system. Active filters are used to reduce voltage and current harmonics produced by computer loads on the supply side. The proposed system is implemented with synchronous reference frame (SRF) theory for extracting compensating current reference. The reference signal obtained by SRF theory is utilized to generate switching pulse for active power filter. The performance of SRF controlled time series neural network is implemented with voltage-controlled active power filter to reduce distortions in the supply side. The system is modelled in MATLAB Simulink environment, and the results of neural network reduce the harmonic current to a minimum level when compared to a traditional PI tuned SRF controller.
ELITE - A Novel Ranking Algorithm for Social Networking Sites Using Generic Scoring Function

Social networks need to manage and control the drift of insane amount of information by filtering and ranking everything in order to ensure they are right there for users’ viewing pleasure. However, the realization of social networks ranking is currently dictated by fairly straightforward optimization algorithms. Hence, there is a need for a newly enhanced and improved ranking algorithm to be formulated since users have been occasionally seeing what they should not. A composition of a generic score and a collective score that would equate to a whopping new-fangled algorithm called E.L. I.T. E. which comprises of five essential elements Engagement-U, Lifetime, Impression, Timeframe and Engagement-O in ensuring a more accurate result for users to see more of what they care about, less of what they do not and more of who they are interested in, less of who they are not. Engagement-U is the affinity between users measured by the relationships and other related interests between them, Lifetime is a trace of users’ past based on their positive, neutral and even negative interactions and actions with other users, Impression is the weight of each object determined by the number of positive responses from users, Timeframe is the timeline scoring technique in which an object naturally loses its value as time passes and Engagement-O is the attraction of users to objects measured between objects and associated interests of users.
The Effects of Torque Magnitude and Stiffness in Arm Guidance Through Joint Torque Feedback

Joint torque feedback is a new and intuitive way of delivering kinesthetic feedback to a person or guiding them during motion tasks via wearable devices. In this study, we performed three experiments to understand how the elbow joint responds to guidance via small torques ( $ < \! 1$ Nm). We first applied open-loop torque pulses to the elbow, and determined the magnitude and delay of the resulting arm motion. Second, we provided pulses of a desired position trajectory in combination with a torque proportional to the error between the joint’s angle and the target angle. We compared the effects of different ratios between the error and applied torque, which is the torque stiffness. Finally, we investigated step inputs from one angle to another in conjunction with different torque stiffnesses. We found that open-loop extensional torques caused large elbow movements, independent of the torque magnitude or duration, while flexional torques caused arm motion proportional to both the magnitude and duration. With position pulses, the highest gain of 0.095 Nm/deg resulted in mean position errors of less than 10 degrees, while the lowest gain of 0.012 Nm/deg resulted in mean position errors of nearly 20 degrees. The higher gains caused the arm to move faster and required higher torques, likely due to masking. The arm had a bandwidth of close to 2 Hz, and step inputs resulted in larger mean errors during flexional motion (15.3 degrees for flexion vs. 9.0 degrees for extension).
Diferentes configuraciones para MobileNet en la detección de tumores cerebrales: Different configurations for MobileNet in the detection of brain tumors

Brain tumor is one of the most serious conditions associated with the brain, where a group of abnormal cells grows out of control. The field of computer vision has experienced a notable boom in the area of biomedical applications with the invention of different techniques in Deep Learning. The classification and detection of brain tumors is a primary task where convolutional neural networks are an alternative solution. But the main drawback of existing techniques is that they are complex with a large number of parameters that contribute to high execution time and high system specifications for implementation. In this article, it is proposed to use MobileNet with different settings in the classifier for the detection of brain tumors, a data set published in KAGGLE with a total of 4432 images has been used. The objective of the study is to obtain high efficiency with the MobileNet architecture that is of low complexity and to propose a system for the classification of brain tumors. With MobileNet as characteristics extractor, it was proposed to use four classifier configurations, as the first classifier, the Softmax function is used that obtained an accuracy of 96.63%, secondly, a Linear classifier was used that obtained an accuracy of 98.59%, in third place, SVM with a linear kernel was used as a classifier, which obtained an accuracy of 97.72%, and finally, SVM with a non-linear kernel was used as a classifier, which obtained 98.04%. With the results, it can be concluded that MobileNet is an excellent option to face this type of medical imaging problems due to its low computational cost and its high level of accuracy in detecting anomalies in the images provided.
Station Device and Network Communications Performance During System Stress Conditions

Automation and protection systems that go beyond the most basic operations require some form of communication between relays and a central processor and between relays themselves. Typical practices in evaluating or specifying the communications capabilities of relays or networks measure the time for a signal to transport from the internal processes of one device, through the network, to the output of another device. While this may be an important measure, it may not reflect operating conditions in the power system. This paper describes research to measure the complete system time to transmit, communicate, receive, and process digital messages in a system used for any automated control or protection purpose. In addition to measuring single bits of data, tests were performed using multiple bits and “data storms” that could be seen during significant system events or disruptions. Complete tests included measurement of processing times within relays, as well as network times to distribute data to multiple devices through point networks. As Ethernet communications increase the ability to exchange information between numerous devices in a station, care needs to be taken to evaluate the system as a whole and not just as a group of points. This paper provides methods to evaluate overall system performance during realistic conditions that could be encountered within installations during test and once in service. Understanding the impact of message size, transmission rate, and multiple device transmissions on system performance are all crucial to optimize system design and set realistic performance expectations.
Design of a Drift Tube Linac for the ISAC Project at TRIUMF

The ISAC radioactive ion beam facility under construction at TRIUMF combines an isotope-separator-on-line with a post accelerator. Required in the accelerator chain is a drift tube linac capable of accelerating unstable nuclei with a post stripper charge to mass ratio of ≥ 1/6 from E = 0.15 MeV/u to a final energy fully variable up to 1.5 MeV/u. Due to the relatively low intensities of some of the ion species continuous (cw) operation of the accelerator is required. A five tank interdigital H-type structure, operating at 105 MHz, has been chosen. The beam dynamics conceptual design and the results of various particle simulations are presented. Computer modelling of the rf structure and model measurements have been completed and are reported.
Research on the Dissemination of Public Opinion on the Internet Based on the News Channels

As the Internet has developed into a ubiquitous source of news and information, the role of other news channels and their impacts on propagation circle are often ignored. In this paper we improve the network communication model based on the infectious disease dynamics theory by introducing a new parameter E, External News Channels into it. The simulation results on Matlab platform show that the new model can describe the characteristics of online communication behavior on social network platform in a more accurate way. In apply of this model, it is possible to analyze the current spreading situation of a topic and evaluate its trends. In need of public opinion guidance, public agencies can decide whether other news channels such as traditional media or information distribution through SMS should be called in.
The Effectiveness of Different Radio Program Formats for the Dissemination of Information on Safe use of Insecticides in Paddy Cultivation in Mahaweli System - C of Sri Lanka

The study was conducted to determine the effectiveness of talk, discussion, interview and drama formats in changing knowledge and attitude of farmers on safe use of insecticides. A research design with a before and after survey with a control group was adopted Representative sample of farmers was selected with the help of cluster sampling combined with simple random sampling techniques. The total sample comprised of 180 farmers with 140 in four treatment groups and 40 in the control group. A fully structured questionnaire with knowledge measures and attitude scale was the main research instrument. Data were gathered at three levels, before, immediately after and one month after treatment. The results suggested that all four formats influence knowledge of farmers immediately as well as after one month However the extent of influence varies on program format and time period after the exposure to instructions. Interview format is the most effective in terms of immediate knowledge gain, while drama, discussion and talk formats follow in order. Discussion format has the highest knowledge retention after one month followed by drama, interview and talk formats. With respect to attitude change, the influence of all formats was much lower compared to that on knowledge. In addition, a relatively high level of attitude change was observed after one month compared to that of immediately after treatment. Only drama format had influenced attitude change significantly.