Miracle-dz/UniFAR-FTUs huggingface dataset:
Invited Paper: Towards Efficient Microservice Communication

Distributed applications on the cloud are being developed and deployed as microservices as opposed to the monolithic architecture. Service Meshes have emerged as a way of specifying communication policies between microservices. Service Meshes have the potential to abstract the networking requirements of distributed applications from the application logic. However, current service mesh frameworks introduce significant performance and resource overheads. We study the overheads of service meshes and make a case for redesigning both the control plane and data plane for service meshes. First, we propose the notion of Application Defined Middleboxes, which makes it possible for the mesh control planes to reduce the overheads by optimizing where to implement application policies. Second, we demonstrate preliminary ideas on accelerating the data plane to further reduce the overheads.
Characterization and application of a lytic jumbo phage ZPAH34 against multidrug-resistant Aeromonas hydrophila

Aeromonas hydrophila is an emerging foodborne pathogen causing human gastroenteritis. Aeromonas species isolated from food such as seafood presented multidrug-resistance (MDR), raising serious concerns regarding food safety and public health. The use of phages to infect bacteria is a defense against drug-resistant pathogens. In this study, phage ZPAH34 isolated from the lake sample exerted lytic activity against MDR A. hydrophila strain ZYAH75 and inhibited the biofilm on different food-contacting surfaces. ZPAH34 has a large dsDNA genome of 234 kb which belongs to a novel jumbo phage. However, its particle size is the smallest of known jumbo phages so far. Based on phylogenetic analysis, ZPAH34 was used to establish a new genus Chaoshanvirus. Biological characterization revealed that ZPAH34 exhibited wide environmental tolerance, and a high rapid adsorb and reproductive capacity. Food biocontrol experiments demonstrated that ZPAH34 reduces the viable count of A. hydrophila on fish fillets (2.31 log) and lettuce (3.28 log) with potential bactericidal effects. This study isolated and characterized jumbo phage ZPAH34 not only enriched the understanding of phage biological entity diversity and evolution because of its minimal virion size with large genome but also was the first usage of jumbo phage in food safety to eliminate A. hydrophila.
A transformer-based approach for early prediction of soybean yield using time-series images

Crop yield prediction which provides critical information for management decision-making is of significant importance in precision agriculture. Traditional manual inspection and calculation are often laborious and time-consuming. For yield prediction using high-resolution images, existing methods, e.g., convolutional neural network, are challenging to model long range multi-level dependencies across image regions. This paper proposes a transformer-based approach for yield prediction using early-stage images and seed information. First, each original image is segmented into plant and soil categories. Two vision transformer (ViT) modules are designed to extract features from each category. Then a transformer module is established to deal with the time-series features. Finally, the image features and seed features are combined to estimate the yield. A case study has been conducted using a dataset that was collected during the 2020 soybean-growing seasons in Canadian fields. Compared with other baseline models, the proposed method can reduce the prediction error by more than 40%. The impact of seed information on predictions is studied both between models and within a single model. The results show that the influence of seed information varies among different plots but it is particularly important for the prediction of low yields.
COVID-19 Fake News Detection in Malaysia – A Supervised Approach

Social media has been flooded with enormous amounts of COVID-19-related information ever since the COVID- 19 pandemic started back in 2020. Since then, Malaysian citizens have become more reliant than ever on social media for consumption of COVID-19 information. However, the lack of COVID-19 news regulations on social media platforms encouraged people to post unverified, fake and misleading COVID-19 related information. Because of the time-consuming nature of fact-checking, people often take these unverified COVID-19 news for granted. Consequently, people inadvertently spread these fake COVID-19 news to their families, friends and relatives on social messaging platforms like WhatsApp. The spread of COVID- 19 fake news online in Malaysia can have severe sequences, causing widespread panic among fellow Malaysians. In this paper, we proposed a supervised learning approach to detect COVID-19 fake news. The fake news on COVID-19 were scraped from the website called Sebenarnya, and real news were scraped from The Star website. We applied a semantic model with different word representations which include Bag of Words (BOW), Term Frequency - Inverse Document Frequency (TF-IDF), Word2Vec and Global Vectors (GloVe). In the evaluation step, 6 supervised machine learning algorithms were applied such as Multinomial Naive Bayes, Support Vector Machines, Decision Tree, Random Forest, Logistic Regression and Adaboost. Afterward, 10-fold cross validation was used to train and evaluate the 6 supervised algorithms according to performance metrics such as accuracy, precision, recall, AUC-ROC, F1-score. The results showed that Random Forest with the word representation of TF-IDF per- formed the best with over 97% accuracy in contrast to numerous conventional supervised machine learning classifiers.
A Combined Method of Determining Weight Based on Maximizing the Membership Decision Function

In order to reflect the information of subjective and objective weight method,a combined method based on maximizing the membership decision function is proposed.According to the idea that final weight should be close to the known weights as much as possible,an optimization model is constructed.And final weight is yield by solving the model.Numerical example is used to illustrate the effectiveness of the new method.
ParSwarm: A C++ Framework for Evaluating Distributed Algorithms for Robot Swarms

Due to the increasing complexity of robot swarm algorithms, analyzing their performance theoretically is often very difficult. Instead, simulators are often used to benchmark the performance of robot swarm algorithms. However, we are not aware of simulators that take advantage of the naturally highly parallel nature of distributed robot swarms. This paper presents ParSwarm, a parallel C++ framework for simulating robot swarms at scale on multicore machines. We demonstrate the power of ParSwarm by implementing two applications, task allocation and density estimation, and running simulations on large numbers of agents.
Molecular and long-term behavioral consequences of neonatal opioid exposure and withdrawal in mice

Introduction Infants exposed to opioids in utero are at high risk of exhibiting Neonatal Opioid Withdrawal Syndrome (NOWS), a combination of somatic withdrawal symptoms including high pitched crying, sleeplessness, irritability, gastrointestinal distress, and in the worst cases, seizures. The heterogeneity of in utero opioid exposure, particularly exposure to polypharmacy, makes it difficult to investigate the underlying molecular mechanisms that could inform early diagnosis and treatment of NOWS, and challenging to investigate consequences later in life. Methods To address these issues, we developed a mouse model of NOWS that includes gestational and post-natal morphine exposure that encompasses the developmental equivalent of all three human trimesters and assessed both behavior and transcriptome alterations. Results Opioid exposure throughout all three human equivalent trimesters delayed developmental milestones and produced acute withdrawal phenotypes in mice reminiscent of those observed in infants. We also uncovered different patterns of gene expression depending on the duration and timing of opioid exposure (3-trimesters, in utero only, or the last trimester equivalent only). Opioid exposure and subsequent withdrawal affected social behavior and sleep in adulthood in a sex-dependent manner but did not affect adult behaviors related to anxiety, depression, or opioid response. Discussion Despite marked withdrawal and delays in development, long-term deficits in behaviors typically associated with substance use disorders were modest. Remarkably, transcriptomic analysis revealed an enrichment for genes with altered expression in published datasets for Autism Spectrum Disorders, which correlate well with the deficits in social affiliation seen in our model. The number of differentially expressed genes between the NOWS and saline groups varied markedly based on exposure protocol and sex, but common pathways included synapse development, the GABAergic and myelin systems, and mitochondrial function.
Cultural accommodation of internet-based interventions for substance use and related disorders: a proposed comprehensive framework based on a pilot study and a literature review

Despite the low utilization rates of substance use and related disorders services, and the ability of internet-based interventions for substance use and related disorders (IBIS) to address challenges related to service engagement, limited attention has been placed on the processes for the accommodation of these interventions to diverse cultural settings. This study aimed to develop a framework for the cultural accommodation of IBIS across populations based on a pilot study and a literature review. A pilot study of cultural accommodation of an existing internet intervention for alcohol use was carried out in Israel, which involved focus groups and daily online surveys of prospective consumers (N = 24) as well as interviews with experts (N = 7) in the substance abuse treatment field. Thematic analysis revealed a range of themes that relate to the general Israeli culture and the specific Israeli drinking subculture, identified as needing to be addressed in the process of intervention accommodation. A comprehensive framework for cultural accommodation of IBIS is suggested, consisting of five stages: Technical and cultural feasibility; Engagement of target group; Identification of accommodation variables, Accommodation, and evaluation of the accommodated intervention. In addition, the framework consists of four dimensions of accommodation: Barriers and facilitators; Audio-visual materials and language; Mechanisms of change; Intersectional factors. We suggest that the proposed framework may serve as a guide for the cultural accommodation of existing internet-based interventions for substance use and related disorders across a range of cultural and geographical settings, thus augmenting the ecological validity of internet-based interventions for substance use and related disorders, expanding cross-cultural intervention research, and reducing health disparities worldwide.
Altered neurovascular coupling in patients with vascular cognitive impairment: a combined ASL-fMRI analysis

Background and objective This study aims to examine the role of neurovascular coupling (NVC) in vascular cognitive impairment (VCI) by investigating the relationship between white matter lesion (WML) burden, NVC, and cognitive deficits. Additionally, we aim to explore the potential of NVC as a tool for understanding the neural mechanisms underlying VCI. Methods This study included thirty-eight small vessel disease cognitive impairment (SVCI) patients, 34 post-stroke cognitive impairment (PSCI) patients, and 43 healthy controls (HC). Comprehensive assessments, including neuroimaging and neuropsychological testing, were conducted to evaluate cognitive function. WML burden was measured and correlated with NVC coefficients to examine the relationship between white matter pathology and NVC. Mediation analysis was employed to explore the link relationship between NVC, WML burden, and cognitive function. Results The present study showed that NVC was significantly reduced in the SVCI and PSCI groups compared with HCs at both whole-brain and brain region level. The analysis revealed notable findings regarding NVC in relation to WML burden and cognitive function in VCI patients. Specifically, reduced NVC coefficients were observed within higher order brain systems responsible for cognitive control and emotion regulation. Mediation analysis demonstrated that NVC played a mediating role in the relationship between WML burden and cognitive impairment. Conclusion This study reveals the mediating role of NVC in the relationship between WML burden and cognitive function in VCI patients. The results demonstrate the potential of the NVC as an accurate measure of cognitive impairment and its ability to identify specific neural circuits affected by WML burden.
THE DEVOLATILIZATION CHARACTERISTICS OF BIOMASS AT HIGH HEATING RATES

Biomass fast pyrolysis technology is one of the most important approach for biomass liquefaction. To study the devolatilization characteristics of biomass at high heating rates(~104 K/s) can make the designing of pyrolysis system more effectively. Some kinds of biomass, such as corn stalks, wheat straw, rice husk, coconut shell, were tested in a plasma heated laminar entrained flow reactor. The first order Arrhenius equation was introduced to simulate the pyrolysis of these kinds of biomass, and the relevant parameters, such as apparent active energy, apparent frequency factor were obtained throuth the experimental data. The results showed that at high heating rates, the above parameters were not related with the heating rates.
Effect of thermal-annealing on the magnetoresistance of manganite-based junctions

Thermal-annealing has been widely used in modulating the oxygen content of manganites. In this work, we have studied the effect of annealing on the transport properties and magnetoresistance of junctions composed of a La0.9. Ca0.1MnO3+δ film and a Nb-doped SrTiO3 substrate. We have demonstrated that the magnetoresistance of junctions is strongly dependent on the annealing conditions: From the junction annealed-in-air to the junction annealed-in-vacuum, the magnetoresistance near 0-V bias can vary from ∼−60% to ∼0. A possible mechanism accounting for this phenomenon is discussed.
Employment of thin thorium films in fission track neutron dosimetry

G. Bigazzil, J. C. Hadler N. ', P. J. Iunes2, T. C. W. P.' Mello2, L. M. S. Navia2, S. R. Paulo3 and A. R. Zúñiga G.214 ' Istituto cli Geocronologia e Geochimica Isotopica, CNR, 56100 Piso, Italy 21nstituto de Física "Gleb Wataghin", Universidade Estadual de Campinas, UNICAMP, C P Gf G 5 , 13083-970 Campinas-SP, Brazil 3Depto. de Física, ICET , IJniversidade Federal de Mato Grosso, UFMT, Av. Fernando Correa, s /n , 78060-900 C u i a b á M T , Brazil Instituto Peruano cle Energia Nuclear, IPEN, Av. Canadá, 1470, Lima 41, Peru
Overview of Electron Cyclotron Heating and Electron Cyclotron Current Drive Launcher Development in Magnetic Fusion Devices

Abstract In any system designed for electron cyclotron (EC) heating (ECH) and EC current drive in fusion plasmas, the launcher is the matching element between the plasma and the transmission line. Only an appropriate launcher achieves efficient use of the gyrotron power for the many different high-power EC H&CD applications. The frontier is now set at ≈4 MW of launched power at 110 to 140 GHz for ≈10 s, to be further moved to ≈10 MW, 1000 s in the near future. ITER will push the limit to 20 MW, 170 GHz. The workhorse of the antenna system is the front steering setup consisting of a movable mirror, or a mirror array, in front of the hot plasma, which provides for full flexibility in the EC H&CD applications. However, because of the concern associated with cooled and movable parts in a hostile environment, an arrangement with movable mirrors positioned far from the vessel port, and connected to the plasma by imaging waveguides, is being developed as a remote steering backup solution. In a reactor, where flexibility is much less relevant than reliability, the situation could reverse. Techniques for a radial scan of the deposition layer different from front beam steering are discussed in this paper. The ideal goal would be a 100% coupling of the launched EC power, to occur within ≈2% of the plasma size and through pipes of size negligible with respect to the vessel, without negative impact on plasma periphery in spite of the high power densities transmitted through the edge.
Search for the production of dark matter candidates in association with heavy dimuon resonance using the CMS open data for proton–proton collisions at √ s (cid:3) 8 TeV

In this work, we present a search for the possible production of Dark Matter particles at the Large Hadron Collider alongside a new hypothetical neutral gauge boson denoted by Z (cid:2) . The topology of the studied events is dimuons plus large missing transverse momentum. The study is performed using the CMS open data samples collected by the CMS experiment in the LHC proton–proton collisions at center-of-mass energy of 8 TeV in 2012, which corresponds to an integrated luminosity of 11.6 fb − 1 , and the corresponding CMS open Monte Carlo samples. Two benchmark scenarios were used for interpreting the data, the Dark Higgs scenario and the effective ﬁeld theory formalism. No evidence for the existence of dark matter candidates was found. 95% conﬁdence level limits are set on the masses of the Z (cid:2) and the cutoff scale of the effective ﬁeld theory.
Cardiac motion signals contained in the Doppler flow tracing and their influence on the measurement of blood flow velocity

Objective To investigate the influence of cardiac motion on the measurement of Doppler blood flow velocity through an in vitro model. Methods An in vitro model was designed to measure and independently control the flow of a liquid through a chamber and the motion of the chamber relative to the Doppler beam. A cornstarch-water slurry was driven by a pulsatile pump through tubing to simulate the blood flow within the heart, and the tubing was cyclically moved by a piston to simulate the heart motion. Results The Doppler spectrum of the combined motion of the chamber and the fluid was the vector sum of their Doppler signals.Conclusion Cardiac motion alters the Doppler signal derived from blood flow and this effect should be considered in the Doppler flow velocity measurement.
High Performance on a Pragmatic Task May Not Be the Result of Successful Reasoning: On the Importance of Eliciting Participants’ Reasoning Strategies

Abstract Formal probabilistic models, such as the Rational Speech Act model, are widely used for formalizing the reasoning involved in various pragmatic phenomena, and when a model achieves good fit to experimental data, that is interpreted as evidence that the model successfully captures some of the underlying processes. Yet how can we be sure that participants’ performance on the task is the result of successful reasoning and not of some feature of experimental setup? In this study, we carefully manipulate the properties of the stimuli that have been used in several pragmatics studies and elicit participants’ reasoning strategies. We show that certain biases in experimental design inflate participants’ performance on the task. We then repeat the experiment with a new version of stimuli which is less susceptible to the identified biases, obtaining a somewhat smaller effect size and more reliable estimates of individual-level performance.
Utility of Cardiac Rehabilitation for Long-Term Outcomes in Patients with Hospital-Acquired Functional Decline after Cardiac Surgery: A Retrospective Study

Hospital-acquired functional decline is an important outcome that affects the long-term prognosis of patients after cardiac surgery. Phase II cardiac rehabilitation (CR) for outpatients is expected to improve prognosis; however, this is not clear in patients with hospital-acquired functional decline after cardiac surgery. Therefore, this study evaluated whether phase II CR improved the long-term prognosis of patients with hospital-acquired functional decline after cardiac surgery. This single-center, retrospective observational study included 2371 patients who required cardiac surgery. Hospital-acquired functional decline occurred in 377 patients (15.9%) after cardiac surgery. The mean follow-up period was 1219 ± 682 days in all patients, and there were 221 (9.3%) cases with major adverse cardiovascular events (MACE) after discharge during the follow-up period. The Kaplan–Meier survival curves indicated that hospital-acquired functional decline and non-phase II CR was associated with a higher incidence of MACE than other groups (log-rank, p < 0.001), additionally exhibiting prognosticating MACE in multivariate Cox regression analysis (HR, 1.59; 95% CI, 1.01–2.50; p = 0.047). Hospital-acquired functional decline after cardiac surgery and non-phase II CR were risk factors for MACE. The participation in phase II CR in patients with hospital-acquired functional decline after cardiac surgery could reduce the risk of MACE.
Task-specific self-supervision for CT image denoising

ABSTRACT CT image quality is largely reliant on radiation dose, which causes a trade-off between image quality and dose, affecting the subsequent image-based diagnostic and treatment performances. Deep learning approaches for low-dose CT image denoising require access to large training sets and specifically the reference full-dose images, which can be difficult to obtain. Self-supervised learning enables learning with reduced reference data burden. Currently available self-supervised CT denoising works are either dependent on foreign domains or pretexts that are not very task-relevant, requiring lots of adjustments (architectural, loss function, training parameters, etc.) and additional skills to perform the downstream denoising task. To tackle the aforementioned challenges, we propose a novel self-supervised pretraining approach, namely Self-Supervised Window-Leveling for Image DeNoising (SSWL-IDN), leveraging an innovative, task-relevant, simple yet effective surrogate – prediction of the window-leveled equivalent. SSWL-IDN leverages residual learning and a hybrid loss combining perceptual loss and MSE, all incorporated in a VAE framework. Our extensive (in- and cross-domain) experimentation demonstrates the effectiveness of SSWL-IDN in aggressive denoising of CT (abdomen and chest) images acquired at two different dose levels (5% and 25%), without requiring any kind of architectural or downstream training adjustments. We have made our code publicly available at https://github.com/ayaanzhaque/SSWL-IDN
Simulation for the Superconductor Linear Eddy Current Brake of the High-Speed Train

A kind of superconductive coil was designed as the linear Eddy current brake for the electric multiple units. Two-dimensional and three-dimensional simulations were carried out on the designed coils. The 2-D simulation results showed that the generated braking force could reach 10 kN when the train speed was between 28 and 110 m/s. The simulation results indicated that the reduced gap between the coil and the railway, the increased pole distance, and the increased coil quantity would bring more braking force. The relationship curve between speed and braking force was also investigated during the 2-D simulation. The speed of 28 and 110 m/s was applied with the 3-D simulation based on the 2-D results. Both the magnetic inducting intensity and the current 180 A could meet the requirements of the chosen superconducting wire.