Miracle-dz/UniFAR-FTUs huggingface dataset:
Micro-Video Popularity Prediction Via Multimodal Variational Information Bottleneck

In this paper, we propose a Hierarchical Multimodal Variational Encoder-Decoder (HMMVED) to predict the popularity of micro-videos by comprehensively leveraging the user information and the micro-video content in a hierarchical fashion. In particular, the multimodal variational encoder-decoder framework encodes the input modalities to a lower dimensional stochastic embedding, from which the popularity of micro-videos can be decoded. Considering the leading role of the user’s social influence in social media for information dissemination, a user encoder-decoder is designed to learn the prior Gaussian embedding of the micro-video from the user information, which is informative about the coarse-grained popularity. In order to incorporate the fluctuation around the coarse-grained popularity caused by the diverse multimodal content, in the micro-video encoder-decoder, the refined posterior distribution of the micro-video embedding is encoded from the content features while encouraged to be close to the learned prior distribution. The fine-grained popularity of each micro-video is decoded from the posterior embedding of the micro-video. Based on the multimodal extension of variational information bottleneck theory, we show that the learned latent embeddings of micro-videos are maximally expressive about the popularity whilst maximally compressing the information from input modalities. Extensive experiments conducted on two real-world datasets demonstrate the effectiveness of the proposed method. Codes and datasets are available at: https://github.com/JennyXieJiayi/HMMVED.
LOW-VELOCITY IMPACT RESPONSES OF FG-GRC SANDWICH BEAMS WITH VISCOELASTIC CORES

The dynamic snap-through and oscillation behaviors are studied of a post-buckled functionally graded graphene reinforced composite (FG-GRC) beam with a viscoelastic core under low-velocity impact. The modified Halpin Tsai meso-mechanical model is used to predict the material properties of FG-GRC. The Hertz point contact model is used to calculate the contact force between the impactor and the post-buckled beam. Considering the axial prestress, the constitutive relations of the composite layer and the Kelvin type viscoelastic constitutive model of the damping layer are proposed. A generalized higher-order shear deformation zig-zag beam theory is utilized to model the nonlinear displacement fields. Based on the Hamilton energy variational principle, the governing equations of dynamics are derived. Through two-step analysis, the post-buckling equilibrium paths are obtained as the initial state condition for the impact problem analysis. Further, combined with the fourth-order Runge Kutta method, the two-step perturbation-Galerkin method is extended to simulate the time history curves of the contact force and the dynamic response curves of the post-buckled beams. Compared with the results based on other beam models, the correctness of the material model, theoretical model and computation method is validated. The dynamic characteristics of bi-stable large amplitude vibration of the post-buckled beams under single and two collisions are studied. The effects of axial load, impact velocity, viscoelastic damping characteristics and impactor materials on the contact force and the deflection time history curves of the post-buckled beams are discussed. The results suggest that the contact force is only sensitive to the impact velocity. A certain structural collision parameter design can change the response of the post-buckled beam from single potential energy trap motion to double trap large oscillation, and the contact force is approximately unchanged. The results of this work can be of reference significance for the design of bi-stable energy capture system with collision.
Localized Damage Detection Algorithm and Implementation on a Large-Scale Steel Beam-to-Column Moment Connection

Civil structures experience loading scenarios ranging from typical ambient excitations to extreme loads induced by natural events that, depending on their intensity, cause damage. It is important to detect damage before it propagates to become detrimental to integrity and functionality of the structure. Significant research efforts are focused on developing damage detection algorithms to diagnose damage from performance and response of the structure. A major challenge in many existing algorithms is in their validation and absence of real-scale implementation. This paper presents implementation of influence-based damage detection algorithm by implementation on a large-scale structural model (steel beam-to-column moment connection) which experiences progressive damage towards collapse of the system through increasing cyclic loading. IDDA utilizes statistical analysis of correlation functions between the structural responses at different locations. It is shown through this implementation that IDDA, accompanied by a statistical framework, can accurately identify structural changes and indicate the intensity of the damage.
CHA2DS2 -VASc score as a predictor for contrast-induced nephropathy in patients with acute coronary syndrome undergoing percutaneous coronary intervention

Contrast induced nephropathy (CIN) is one of the most important complications of PCI, resulting in increased medical resources, longer hospital stay and higher mortality so it is important to detect early high risk patients for CIN and provide them with preventive measures. In recent years, several studies have demonstrated an association of CHA2DS2-VASc score with cardiovascular prognosis and adverse outcomes in different populations including heart failure, SCAD and ACS beyond the original AF field. The predictive value of the CHA2DS2-VASc score on CIN still remains unclear although all of the components of the CHA2DS2-VASc score are important risk factors for CIN. For this reason, the present study was designed to evaluate the predictive value of preprocedural CHA2DS2-VASc score on the development of CIN in patients with ACS who underwent PCI. To assess the predictive value of the CHA2DS2-VASc Score for contrast induced nephropathy among acute coronary syndrome patients who underwent percutaneous coronary intervention. This study is a prospective study conducted over 300 patients with myocardial infarction underwent primary coronary intervention. It took place from February 2020 till September 2020. We analyzed patient's demographic data, clinical data, laboratory data, angiographic data and CHADSVASC score and followed up patients daily for 72 hour after PCI for development of CIN then compared these data in CIN versus non CIN patients trying to find out which of these factors can predict occurrence of CIN and find CHADSVASC score cutoff value for prediction of CIN. CIN was developed in 89 patients. A significant relationship existed between CIN and female gender, DM, HTN, door to needle time, killip class above one, contrast volume (p<0.000), previous intervention using contrast (p<0.001), anemia (p<0.014), duration of procedure (p<0.074) and number of coronary vessels affected (p<0.031). However, non-significant relationship existed between CIN and Stroke, TIA, previous thromboembolism (p<0.446), ejection fraction (p<0.155), culprit vessel (p<0.317), TIMI grade (p<0.278) and antiplatelet type (p<0.934). Receiver operating characteristic curve analysis showed good predictive value of CHA2DS2-VASc score for CIN (area under the curve 0.801, sensitivity 69.66% and specificity 80.75%). Patients with a CHA2DS2-VASc score cutoff value ≥4 had a higher liability for CIN (p<0.000). CHA2DS2-VASc score is a simple bedside risk score for preprocedure CIN risk stratification among ACS patients who underwent primary PCI. Type of funding sources: None.
Molecular cloning, functional characterization, tissue expression and polymorphism analysis of buffalo PRDX6 gene

PRDX6 is a bifunctional protein involved in antioxidant regulation and phospholipid metabolism. Previous studies have shown that PRDX6 is involved in some biological pathways and networks related to lactation. The aim of this study was to explore the characteristics, function, tissue expression and variation of buffalo PRDX6 gene. We cloned and characterized the complete coding sequence (CDS) of buffalo PRDX6. The CDS of PRDX6 for swamp and river buffalo is the same, which consists of 675 nucleotides and encodes a protein of 224 amino acids. Buffalo PRDX6 contains one PRX_1cys functional domain (AA 7–222), which is probably related to the regulation of oxidative stress. Multi-tissue differential expression analysis showed that buffalo PRDX6 was highly expressed in the muscle, brain, lung and small intestine during non-lactation and lactation, and there were significant differences in expression in all the tissues except the small intestine between the two periods. It is worth noting that the mRNA abundance of buffalo PRDX6 in non-lactating mammary gland is higher than that in lactating mammary gland. Among the two single nucleotide polymorphisms (SNPs) identified in the CDS in this study, c.261C>T is shared by the two types of buffalo with different allelic frequencies, and c.426T>G is found only in river buffalo. The c.426T>G is non-synonymous, resulting in the amino acid substitution p.Asn142Lys. Only one nucleotide differential site is identified in PRDX6 gene between buffalo and other species of Bovidae. Phylogenetic analysis indicated that buffalo PRDX6 has a closer genetic relationship with that of the species in Bovidae. These results indicate that PRDX6 probably plays a crucial role in the mammary gland of buffalo. This study provides the foundation for further functional studies of PRDX6 in buffalo.
The Determinants of Non-COVID-19 Excess Deaths During the COVID-19 Pandemic: A Cross-country Panel Study

This paper examines the determinants of non-COVID excess deaths during the COVID pandemic between January and June 2020. These are the extra deaths occurring during the pandemic which are not directly attributable to COVID. While emerging literature examines the determinants of COVID deaths, few look at non-COVID excess deaths, though early estimates suggest they are enough to be seen as a pandemic in their own count. We investigate the impact of factors including COVID deaths and cases, lockdown stringency, economic support and search intensity for non-COVID conditions on excess deaths, using Fixed Effects and GMM estimations. We also use quantile regression to assess the differential impacts of the variables at different stages of the excess death distribution. First, we find that excess deaths are increasing and concave in COVID deaths, and that the rate of growth, as well as the level, of COVID deaths has a significant and positive impact. Second, we find some evidence that stringency of lockdown increases excess deaths by a maximum of 16 extra per-million population. Third, we find a reduction in search intensity for other conditions significantly increases excess deaths, implying that policymakers should ensure public health messaging for other conditions during a pandemic. JEL Classifications: I12, I18, I11
State feedback control strategy and voltage balancing scheme for a transformer-less STATic synchronous COMpensator based on cascaded H-bridge converter

In this study, a transformer-less STATic synchronous COMpensator (STATCOM) based on cascaded H-bridge (CHB) multilevel converter with floating DC links is presented. This study introduces a control strategy based on state feedback control algorithm in order to supply reactive power to the grid and to compensate the total losses in the internal H-bridge cells. Using this strategy, the converter stability and the fast dynamic response are guaranteed. Moreover, a voltage balancing strategy is proposed, which not only regulates the DC-link voltage of H-bridge cells to the reference value, but also evenly distributes total reactive power among the converter cells, even when there is difference between the losses of H-bridge cells. A 21-level CHB-based STATCOM is simulated in PSCAD/EMTDC environment to evaluate the performance and effectiveness of the new control strategy. Furthermore, the validity of new method is verified on a down-scaled 7-level CHB prototype.
A Study on the Transcriptional Profile of NOS2 and IFN-γ Genes in River Buffalo with Endometritis

Background and Aim: Uterine lumen contamination with bacteria is ubiquitous in buffalo after parturition. Nearly one-third of these infected animals develop endometritis which leads to reduced fertility. The present study aimed to evaluate the expressions of IFN-γ and NOS2 genes in uterine tissue of buffaloes with endometritis and comparing them with those in healthy animals using RT-qPCR Materials and Methods: Uterine samples were collected from 50 apparently healthy and 50 clinically infected buffaloes. RNA was extracted from the collected buffalo's uteri and cDNA was synthesized from extracted RNA. Quantitative Real Time PCR technique was performed using this synthesized cDNA. Results: Apparent up-regulation of both genes mRNA expression was recorded in endometritis-infected animals with 8.3-folds for IFN-γ and 9.99-folds for NOS2 (P<0.001). Conclusion: The upregulation of IFN-γ and NOS2 expression in the uterine tissue of endometritis-infected buffaloes can be used as a scale for measuring the efficiency of drugs used for endometritis treatment.
Prevalence of Mineral Bone Disease in Dialysis Patients

Progressive loss of kidney function in chronic kidney disease (CKD) leads to reduced production of 1-α-(OH)2-D3 (1,25-dihydroxyvitamin D; calcitriol) and abnormal mineral homeostasis leading to bone mineral disorders. The disorder starts with stage 2 CKD but manifests itself as the disease progresses until stage 3 CKD. Material and methods This study was carried out on 61 patients with end-stage renal disease on regular HD at our Centre. After obtaining informed consent, complete blood count, blood urea level, serum creatinine level, albumin level, uric acid level, Ca level, phosphate level, alkaline phosphatase level, and PTH level were done. Results Out of 60 patients 41 (68.33%) were high bone turnover,10 (16.6%) were normal bone turnover whereas 9(15%) were low bone turnover. Conclusion The prevalence of CKD-MBD among dialysis patients is 83.33% at our center and needs proper monitoring by routine investigations including serum phosphate, calcium, vitamin D levels and most importantly i-PTH levels according to guidelines.
Social science, technical systems, and cooperative work: beyond the great divide

From the Publisher: The "great divide" between the approaches of systems developers and those of social scientists to computer supported cooperative work has been vigorously debated in the systems development literature. In spite of their differences in style, the two groups have been cooperating more and more in the last decade, as the "people problems" associated with computing become increasingly evident to everyone. This book is the first to address directly the problem of how to bridge the divide. It offers an exciting overview of the cutting edge of research and theory, and will constitute a solid foundation for the rapidly coalescing field of social informatics.
Modified Mechanical Structure Electric Bike Design Computation and Prototype Model Implementation

The aim of this paper is to investigate the design computation and prototype model implementation of a Modified Mechanical Structure (MMS) Electric Bike (E-Bike). It is the technology that allows the vehicle to operate with the assistance of electrical energy. All conventional cars will be converted to electric vehicles (EVs) in the future. EVs will be affordable to all types of people, allowing them to fly comfortably and safely. As a result, this paper proposes a design estimate and model implementation of the MMS E-Bike with the smallest number of parts, lowest expense, and lightest weight possible. The most important parts of the designed MMS E-Bike are the battery, MMS, BLDC motor, and electronic commutator with their controller. Because of its adapted mechanical frame nature, the designed E-Bike is low in cost and weight, and it can also go up to 25 kmph. Furthermore, the rider will be able to ride the built MMS E-Bike without any pain to their bodies and should be able to sit comfortably during their journey. In comparison to the Ampere Angel and DMW Electra 20 E-Bikes, the performance of the developed model is tested under various operating conditions, as well as their battery backup.
Subway Obstacle Perception and Identification Method Based on Cloud Edge Collaboration

The traditional analysis method of train obstacle uses isomorphic sensors to obtain the state information and completes detection and identification analysis at the remote end of a network. A single data sample and more processing links will reduce the accuracy and speed analysis for subway encountering obstacles. To solve this problem, this paper proposes a subway obstacle perception and identification method based on cloud edge cooperation. The subway monitoring cloud platform realizes the training and construction of a detection model, and the network edge side completes the situation awareness of track state and real-time action when the train encounters obstacles. Firstly, the railroad track position is detected by cameras, and subway running track is identified by Mask RCNN algorithm to determine the detection area of obstacles in the process of subway train running. At the edge of network, the feature-level fusion of data collected by sensor cluster is carried out to provide reliable data support for detection work. Then, based on the DeepSort and YOLOv3 network models, the subway obstacle detection model is constructed on the subway monitoring cloud platform. Moreover, a trained model is distributed to the network edge side, so as to realize the fast and efficient perception and action of obstacles. Finally, the simulation verification is implemented based on actual collected datasets. Experimental results show that the proposed method has good detection accuracy and efficiency, which maintains 98.9% and 1.43 s for obstacle detection accuracy and recognition time in complex scenes.
Generalized aptheria and automutilization of members in budgegarigar (Melopsittacus undulatus SHAW, 1805) presenting circovirosis in the Northeast of Brazil

The budgegarigar (Melosittacus undulatus Shaw, 1805) is a bird of the order Psittaciformes and family Psittaculidae. This species is considered the third most popular pet in the world and is frequently seen in veterinary clinics. Among the diseases that can affect these animals, the Psittacidae beak and feather disease (PBFD), or circovirosis, is an infectious disease commonly reported in some regions. This paper aims to describe the case of a budgegarigar presenting generalized aptheria and self-mutilation of limbs due to PBFD and feather-picking disorder in Northeastern Brazil. A budgegarigar was admitted to the Veterinary Hospital of the Federal Rural University of the Semiarid (HOVET-UFERSA) with generalized aptheria. Subsequently, feces were collected and a molecular polymerase chain reaction (PCR) analysis for PsCV Circovirus was requested. The result was positive, and upon the animal's return to the clinic, it presented right carpometacarpal and tarsometatarsal self-mutilated. Considering that reports of these disorders for psittacidae are scarce in the Northeast, we report the first occurrence of circovirosis and consequent feather-pulling disorder with clinical manifestation of generalized aptheria and self-mutilation of limbs in a budgegarigar in the state of Rio Grande do Norte, which represents a risk for the conservation of wild Psittacidae in this region.
A Mathematical Model for Driver Steering Control, with Design, Tuning and Performance Results

A mathematical model for the steering control of an automobile is described. The structure of the model derives from linear optimal discrete time preview control theory but it is non-linear. Its parameter values are obtained by heuristic methods, using insight gained from the linear optimal control theory. The driver model is joined to a vehicle dynamics model and the path tracking performance is demonstrated, using moderate manoeuvring and racing speeds. The model is shown to be capable of excellent path following and to be robust against changes in the vehicle dynamics. Application to the simulation of manoeuvres specified by an ideal vehicle path and further development of the model to formalise the derivation of its parameter values and to put it to other uses are discussed.
Realising Roma rights through a high-stakes history test: Secondary school students narrating the Swedish Roma past, present and future

Building on theories of historical justice, reconciliation and transformative change, this article investigates how 293 secondary school students make sense of the difficult past, present and future of the Romani in a national history test. Using qualitative and quantitative text analysis, this study seeks to explore whom students foreground as agents of change in regard to the Roma past, present and future. Considering the past and looking to the future, the inquiry led students to narrate four scenarios: no change; a regression to a past state of no rights; a development for the better; a future free from oppression. While the students underscored the importance of a shared responsibility for Roma rights, they stressed the nation state as the single most important agent of change for Roma rights in the present and future. Against the backdrop of justice and change, this study argues that while students realise and recognise Roma rights through their narrational practices, and thus may become empowered to act for a just future, these narratives also re-establish historical cultural and ethnic group boundaries which potentially may disempower young learners.
Predicting the CO 2 Emission of Concrete Using Statistical Analysis

Accurate assessment of CO2 emission from buildings requires gathering CO2 emission data of various construction materials. Unfortunately, the amount of available data is limited in most countries. This study was conducted to present the CO2 emission data of concrete, which is the most important construction material in Korea, by conducting a statistical analysis of the concrete mix proportion. Finally, regression models that can be used to estimate the CO2 emission of concrete in all strengths were developed, and the validity of these models was evaluated using 24 and 35MPa concrete data. The validation test showed that the error ratio of the estimated value did not exceed a maximum of 5.33%. This signifies that the models can be used in acquiring the CO2 emission data of concrete in all strengths. The proposed equations can be used in assessing the environmental impact of various construction structural designs by presenting the CO2 emission data of all concrete types.