Miracle-dz/UniFAR-FTUs huggingface dataset:
Low Reynolds number hydrodynamics: with special applications to particulate media

One studying the motion of fluids relative to particulate systems is soon impressed by the dichotomy which exists between books covering theoretical and practical aspects. Classical hydrodynamics is largely concerned with perfect fluids which unfortunately exert no forces on the particles past which they move. Practical approaches to subjects like fluidization, sedimentation, and flow through porous media abound in much useful but uncorrelated empirical information. The present book represents an attempt to bridge this gap by providing at least the beginnings of a rational approach to fluid particle dynamics, based on first principles. From the pedagogic viewpoint it seems worthwhile to show that the Navier-Stokes equations, which form the basis of all systematic texts, can be employed for useful practical applications beyond the elementary problems of laminar flow in pipes and Stokes law for the motion of a single particle. Although a suspension may often be viewed as a continuum for practical purposes, it really consists of a discrete collection of particles immersed in an essentially continuous fluid. Consideration of the actual detailed boundary value problems posed by this viewpoint may serve to call attention to the limitation of idealizations which apply to the overall transport properties of a mixture of fluid and solid particles. "
Characterization of miRNAs in Milk Small Extracellular Vesicles from Enzootic Bovine Leukosis Cattle

Enzootic bovine leukosis (EBL) is a B-cell lymphosarcoma caused by the bovine leukemia virus (BLV). Most BLV-infected cattle show no clinical signs and only some develop EBL. The pathogenesis of EBL remains unclear and there are no methods for predicting EBL before its onset. Previously, it was reported that miRNA profiles in milk small extracellular vesicles (sEVs) were affected in cattle in the late stage of BLV infection. It raised a possibility that miRNA profile in milk sEVs from EBL cattle could be also affected. To characterize the difference in milk of EBL cattle and healthy cattle, we examined the miRNA profiles in milk sEVs from four EBL and BLV-uninfected cattle each using microarray analysis. Among the detected miRNAs, three miRNAs—bta-miR-1246, hsa-miR-1290, and hsa-miR-424-5p—which were detectable using quantitative real-time PCR (qPCR) and are associated with cancers in humans—were selected as biomarker candidates for EBL. To evaluate the utility of these miRNAs as biomarkers for EBL, their levels were measured using milk that was freshly collected from 13 EBL and seven BLV-uninfected cattle. bta-miR-1246 and hsa-miR-424-5p, but not hsa-miR-1290, were detected using qPCR and their levels in milk sEVs from EBL cattle were significantly higher than those in BLV-uninfected cattle. bta-miR-1246 and hsa-miR-424-5p in sEVs may promote metastasis by targeting tumor suppressor genes, resulting in increased amounts in milk sEVs in EBL cattle. These results suggest that bta-miR-1246 and hsa-miR-424-5p levels in milk sEVs could serve as biomarkers for EBL.
Regional Economic Disparities in Europe: Time-Series Clustering of NUTS 3 Regions

The aim of this research is to identify the regional economic disparities in the level of economic wealth and its dynamics in the NUTS 3 regions in EU28 over the period from 2000 to 2017. By performing a time-series clustering analysis at NUTS 3 level, we expect to uncover the economic disparities that might have been hidden in the aggregate NUTS 2 regions. Our results indicate that at a finer spatial scale (NUTS 3 level) disparities flourish, particularly in the period after the global crisis of 2008, in which different recovery rates are observed. In general, NUTS 2 regions tend to spatially cluster at the national level and, although NUTS 3 regions show slightly this tendency as well, the spatial effect is not as strong as it is for NUTS 2 level, revealing specific behaviours of the local economies and markets that remain hidden at the aggregate NUTS 2 level.
The Significance of Convection in Supraglacial Debris Revealed Through Novel Analysis of Thermistor Profiles

Melt from debris‐covered glaciers represents a regionally important freshwater source, especially in high‐relief settings as found in central Asia, Alaska, and South America. Sub‐debris melt is traditionally predicted from surface energy balance models that determine heat conduction through the supraglacial debris layer. Convection is rarely addressed, despite the porous nature of debris. Here we provide the first constraints on convection in supraglacial debris, through the development of a novel method to calculate individual conductive and nonconductive heat flux components from debris temperature profile data. This method was applied to data from Kennicott Glacier, Alaska, spanning two weeks in the summer of 2011 and two months in the summer of 2020. Both heat flux components exhibit diurnal cycles, the amplitude of which is coupled to atmospheric conditions. Mean diurnal nonconductive heat flux peaks at up to 43% the value of conductive heat flux, indicating that failure to account for it may lead to an incorrect representation of melt rates and their drivers. We interpret this heat flux to be dominated by latent heat as debris moisture content changes on a diurnal cycle. A sharp afternoon drop‐off in nonconductive heat flux is observed at shallow depths as debris dries. We expect these processes to be relevant for other debris‐covered glaciers. Debris properties such as porosity and tortuosity may play a large role in modulating it. Based on the present analysis, we recommend further study of convection in supraglacial debris for glaciers across the globe with different debris properties.
Drift and Meander of Spiral Waves

In this thesis, we are concerned with the dynamics of spiral wave solutions to Reaction-Diffsion systems of equations, and how they behave when subject to symmetry breaking perturbations. We present an asymptotic theory of the study of meandering (quasiperiodic spiral wave solutions) spiral waves which are drifting due to symmetry breaking perturbations. This theory is based on earlier theories: the 1995 Biktashev et al theory of drift of rigidly rotating spirals, and the 1996 Biktashev et al theory of meander of spirals in unperturbed systems. We combine the two theories by first rewriting the 1995 drift theory using the symmetry quotient system method of the 1996 meander theory, and then go on to extend the approach to meandering spirals by considering Floquet theory and using a singular perturbation method. We demonstrate the work of the newly developed theory on simple examples. We also develop a numerical implementation of the quotient system method, demonstrate its numerical convergence and its use in calculations which would be difficult to do by the standard methods, and also link this study to the problem of calculation of response functions of spiral waves.
Effect of positional role on isokinetic muscles torque production of selected movements of basketball players

The present study compare the isokinetic torque production of major movements like knee extension, shoulder flexion and elbow extension among different playing position players in basketball and to find out whether positional role effect the muscular strength attribute of players.21 national level basketball players participated in the study voluntarily. For each player measurement of height, weight, age, and training age were taken, the test of isokinetic exercise for knee extension, shoulder flexion, and elbow extension was performed. The study found that the center performs significantly better than forward and guard players for knee extension and shoulder flexion movement and forward perform significantly better than guard for the same. No significant difference was found for elbow extension movement, but after normalization of isokinetic peak torque with body size, comparison of relative isokinetic peak torque showed that center and forward significantly perform better than guard players for isokinetic knee extension movement at 60os-1, whereas guard and forward players significantly perform better than a center player for elbow extension movement at 60os-1. Normalization for body size nullifies the significant difference in isokinetic peak torque produced for shoulder flexion movement at 60os-1.
Cathelicidins Induce Toll-Interacting Protein Synthesis to Prevent Apoptosis in Colonic Epithelium

Cathelicidin peptides secreted by leukocytes and epithelial cells are microbicidal but also regulate pathogen sensing via toll-like receptors (TLRs) in the colon by mechanisms that are not fully understood. Herein, analyses with the attaching/effacing pathogen Citrobacter rodentium model of colitis in cathelicidin-deficient (Camp−/−) mice, and colonic epithelia demonstrate that cathelicidins prevent apoptosis by sustaining post-transcriptional synthesis of a TLR adapter, toll-interacting protein (TOLLIP). Cathelicidins induced phosphorylation-activation of epidermal growth factor receptor (EGFR)-kinase, which phosphorylated-inactivated miRNA-activating enzyme Argonaute 2 (AGO2), thus reducing availability of the TOLLIP repressor miRNA-31. Cathelicidins promoted stability of TOLLIP protein via a proteosome-dependent pathway. This cathelicidin-induced TOLLIP upregulation prevented apoptosis in the colonic epithelium by reducing levels of caspase-3 and poly (ADP-ribose) polymerase (PARP)-1 in response to the proinflammatory cytokines, interferon-γ (IFNγ) and tumor necrosis factor-α (TNFα). Further, Camp−/− colonic epithelial cells were more susceptible to apoptosis during C. rodentium infection than wild-type cells. This antiapoptotic effect of cathelicidins, maintaining epithelial TOLLIP protein in the gut, provides insight into cathelicidin’s ability to regulate TLR signaling and prevent exacerbated inflammation.
Seroprevalence and associated risk factors of Neospora caninum in cattle in the Khomas region of Namibia

Neospora caninum is a coccidian parasite which occurs worldwide and is one of the most important causes of abortion, especially in cattle. However, no studies have been done in Namibia to determine the N. caninum status in livestock. Therefore, this study aimed to determine the seroprevalence level of N. caninum in cattle and the associated risk factors in the Khomas region of Namibia. Seven hundred thirty-six (736) serum samples were collected from female cattle in 32 farming establishments. These comprised 698 beef and 38 dairy cattle sera and were tested using a commercial IDEXX Neospora X2® ELISA kit. Questionnaires were concurrently administered to determine possible risk factors associated with N. caninum seropositivity. A total of 42 sera were positive (all beef), giving an animal-level seroprevalence rate of 5.7%. Eight of the 32 establishments had at least one positive animal, giving a herd-level seroprevalence of 25%. There was no signi�cant association between seropositivity and the presence of dogs, jackals, history of abortions, farm size, number of cattle or average annual rainfall. The establishments with moderate to high numbers of Feliformia were 9.8 times more likely to be seropositive to N. caninum than those with none to low levels of the former (p = 0.0245). The authors concluded that the seroprevalence level of N. caninum in the Khomas region was relatively low compared to other parts of the world and that the role of Feliformia in the epidemiology of bovine neosporosis needed to be further investigated.
Effects of laryngeal manipulations on voice gender perception

This study aims to identify laryngeal manipulations that would allow a male to approximate a female-sounding voice, and that can be targeted in voice feminization surgery or therapy. Synthetic voices were generated using a three-dimensional vocal fold model with parametric variations in vocal fold geometry, stiffness, adduction, and subglottal pressure. The vocal tract was kept constant in order to focus on the contribution of laryngeal manipulations. Listening subjects were asked to judge if a voice sounded male or female, or if they were unsure. Results showed the expected large effect of the fundamental frequency (F0) and a moderate effect of spectral shape on gender perception. A mismatch between F0 and spectral shape cues (e.g., low F0 paired with high H1-H2) contributed to ambiguity in gender perception, particularly for voices with F0 in the intermediate range between those of typical adult males and females. Physiologically, the results showed that a female-sounding voice can be produced by decreasing vocal fold thickness and increasing vocal fold transverse stiffness in the coronal plane, changes in which modified both F0 and spectral shape. In contrast, laryngeal manipulations with limited impact on F0 or spectral shape were shown to be less effective in modifying gender perception.
A Long Short-Term Memory-Based Approach for Detecting Turns and Generating Road Intersections from Vehicle Trajectories

Owing to the widespread use of GPS-enabled devices, sensing road information from vehicle trajectories is becoming an attractive method for road map construction and update. Although the detection of intersections is critical for generating road networks, it is still a challenging task. Traditional approaches detect intersections by identifying turning points based on the heading changes. As the intersections vary greatly in pattern and size, the appropriate threshold for heading change varies from area to area, which leads to the difficulty of accurate detection. To overcome this shortcoming, we propose a deep learning-based approach to detect turns and generate intersections. First, we convert each trajectory into a feature sequence that stores multiple motion attributes of the vehicle along the trajectory. Next, a supervised method uses these feature sequences and labeled trajectories to train a long short-term memory (LSTM) model that detects turning trajectory segments (TTSs), each of which indicates a turn occurring at an intersection. Finally, the detected TTSs are clustered to obtain the intersection coverages and internal structures. The proposed approach was tested using vehicle trajectories collected in Wuhan, China. The intersection detection precision and recall were 94.0% and 91.9% in a central urban region and 94.1% and 86.7% in a semi-urban region, respectively, which were significantly higher than those of the previously established local G* statistic-based approaches. In addition to the applications for road map development, the newly developed approach may have broad implications for the analysis of spatiotemporal trajectory data.
Spoken-Text-Style Transfer with Conditional Variational Autoencoder and Content Word Storage

Text style transfer is the task of converting textual style while preserving content. Content preservation is still challenging in text style transfer under the training condition with non-parallel data. We improve the content preservation performance of text style transfer using a labeled non-parallel corpus, targeting interest styles for text-to-speech synthesis. We propose a content word storage mechanism to preserve “content words”, particularly for improving content preservation, and incorporate it in the conditional variational autoencoder to capture the style information from the labeled non-parallel corpus. We have conducted a bi-directional transfer experiment of Japanese texts about “disfluency removal/insertion” and “standard/Kansai dialect conversion” as target styles. From the results of automatic and human evaluations, we found that 1) the proposed method improved the content preservation without compromising other performances and 2) the proposed method had different performances depending on the direction of style transfer.
LEAN MANUFACTURING AND FINANCIAL PERFORMANCE: A CASE OF MALAYSIAN AUTOMOBILE INDUSTRY

Purpose: It is not necessary that massive investment in automobile industry is beneficial for all the nations. Some countries like Malaysia are facing different issues regarding Financial Performance (FP) due to the intensity of worldwide competition. To address this issue, this study is being conducting to investigate the role of lean manufacturing in the FP of Malaysian automobile industry. Design/Methodology/Approach: This study followed quantitative research approach and survey was preferred to collect required data from managerial staff of Malaysian automobile company with the help of questionnaire. Total 500 questionnaires were used and distributed with the help of simple random sampling technique. Study utilized PLS-SEM to investigate end the impact of lean manufacturing on FP of Malaysian Automobile Industry. Findings: Results of the study revealed a strong connection between lean manufacturing and FP. Lean manufacturing has positive impact on FP of Malaysian automobile industry. Moreover, quality management is important to sustain the link between lean manufacturing and FP. Implications/Originality/Value: This study is contributed in the body of knowledge by highlighting the lean manufacturing practices to promote FP. As this study highlighted various lean manufacturing practices to enhance FP, therefore, it is significant for practitioners
Discriminating Earthquakes From Quarry Blasts Using Capsule Neural Network

Discrimination between earthquakes and quarry blasts is crucial for precise seismic analysis, e.g., seismic hazard mitigation and earthquake cataloging. However, the discrimination process is challenging due to the similarity of waveforms between the local earthquakes and quarry blasts. We propose to use the scalogram and the capsule neural network to distinguish between earthquakes and quarry blasts. First, we obtain the scalogram for 60 s three-channel waveforms, where we extract 10 s before and 50 s after the first arrival time of the seismic event. Second, we utilize the capsule neural network to extract the important information from the input scalogram which leads to robust classification performance. The proposed capsule neural network consists of the convolutional layer, primary capsule layer, and digit caps layer. The convolutional layer extracts the important information from the input data, and the primary capsule layer extracts the spatial relationship between different feature maps. Third, we use the dynamic routing process to connect the primary capsule to the digit caps layer. We train and test the proposed capsule network using a small and unbalanced dataset which is recorded by the Egyptian Seismic Network (ENSN) in the Red Sea and the surrounding area in Egypt. Accordingly, the proposed method achieves a test accuracy of 96.08%. The proposed method is compared to the benchmark methods, i.e., convolutional neural network (CNN), AlexNet, VGG, and ResNet networks, and demonstrated to outperform all of the competing methods. Finally, we apply the proposed method to classify real-time seismic events and obtain promising results.
There is a Brown Dwarf Desert of Companions Orbiting Stars between 75 and 1000 AU

We present results of the first large (> 100 stars) infrared coronographic search for substellar companions to nearby stars. The search consisted of two surveys of stars chosen for their youth and proxim-ity to Earth: 1. ) a 178 star infrared survey at Steward and Lick Observa-tories, with optical followup from Keck Observatory, capable of detecting companions with masses greater than 30MJ, orbiting between about 75 and 300 AU, 2. ) a 102 star survey using the Keck telescope, capable of detecting extrasolar brown dwarfs and planets typically more massive than 10 M J , orbiting between about 75 and 300 AU. This research resulted in the discovery of one brown dwarf companion, zero planets and 23 double stars. The frequency of brown dwarf companions (of any mass) to G, K·and M stars orbiting between 75 and 300 AU is measured to be 1 ± 1 %. The frequency of massive (> 30 MJ) brown dwarf companions is found to be 0.6 ± 0.6 %. The frequency of giant planets with masses larger than 10 MJ, between 75 and 300 AU, is measured here for the first time to be no more than about 3 %.
Event-triggered stabilisation of sampled-data singular systems: a hybrid control approach

This paper provides a design of event-triggered feedback stabilisation scheme for a class of sampled-data singular systems, in which the input matrix corresponding to the algebraic equation is not full column rank. First, unlike the conventional piecewise-constant sampled-data feedback controller, a novel hybrid impulsive and sampled-data state feedback controller is designed, which can effectively match with the algebraic equation at sampling instants. An improved discrete event-triggering mechanism with checking period is proposed to achieve exponential stabilisation. Based on these, by applying the input delay approach and defining a new input-delay dependent Lyapunov functional, a sufficient stability condition is presented which ensures that the solution of the event-triggered control system exists and is unique, and the system is exponentially stable with definite decay rate. The estimate of decay coefficient is also given explicitly. Then, an optimisation-based method is developed to jointly design the hybrid controller gains and the event parameters. Finally, two simulation examples including a linearised 2-generator and 6-bus power network system are given to illustrate the validity of the new approach.
Sentiment analysis of Indian Tweets about Covid-19 vaccines

People are becoming more reliant on social media networks to express their opinions about various topics and obtain health information. The study is intended to explore and analyse the sentiments of Indian people related to Covid-19 vaccines as well as to visualise the top most frequently occurring terms individuals have used to communicate their ideas on Twitter about Covid-19 vaccines in India. The Tweet Archiver was used to retrieve the Tweets against ‘Covid19vaccine’ and ‘Coronavirusvaccine’ hashtags for the period of 2 months 18 days (4 January 2021–22 March 2021). After collecting data, the Orange software and VOSviewer were used for further analysis. The Tweets were posted across the country, with an immense contribution from Maharashtra (223, 15.58%), followed by Delhi (220, 15.37%) and Tamil Nadu (73, 5.10%). The majority (639, 44.65%) of the Tweets reflect positive sentiments, followed by neutral (521, 38.50%) and negative (241, 16.84%) sentiments, respectively. This signifies that most Twitter users have a favourable opinion towards Covid vaccines in India. Based on the relevance score of the words, the words ‘Delhi heart’, ‘Lung institute’, ‘Gift’, ‘Unite2fightcorona’, and ‘Covid-19 Vaccine’ are the leading words appearing in Tweets. The study illustrates the sentiments of the Indian people towards ‘Covid-19 vaccines’, gains some insights into overall public communication about the topic and complements the existing literature. It can assist health policymakers and administrators in better understanding the polarity (positive, negative, and neutral) of Tweets about Covid-19 vaccines on Twitter to raise public awareness about health concerns and misinformation about the vaccine.