Miracle-dz/UniFAR-FTUs huggingface dataset:
Stefan blowing, navier slip and radiation effects on thermo-solutal convection from a spinning cone in an anisotropic porous medium

Thermal radiation features in many high temperature materials processing operations. To evaluate the influence of radiative flux on spin coating systems, we consider herein the thermo-solutal (coupled heat and mass transfer) in steady laminar boundary layer natural convection flow from a rotating permeable vertical cone to an anisotropic Darcian porous medium. Surface slip effects are also included in the model presented. The conservation equations are rendered into self-similar form and solved as an ordinary differential two-point boundary value problem with surface and free stream boundary conditions using MAPLE 17 software. The transport phenomena are observed to be controlled by ten parameters, viz primary and secondary Darcy numbers (Dax and Da), rotational (spin) parameter (NR), velocity slip parameter (a), suction/injection parameter (S), thermal slip parameter (b), mass slip parameter (c) buoyancy ratio parameter (N), and conduction-radiation parameter (Rc). Tangential velocity and temperature are observed to be enhanced with greater momentum slip whereas swirl velocity and concentration are reduced. Increasing swirl Darcy number strongly accelerates both the tangential and swirl flow and also heats the regime whereas it decreases concentrations. Conversely a rise in tangential Darcy number accelerates only the tangential flow and decelerates swirl flow, simultaneously depressing temperatures and concentrations. Increasing thermal slip accelerates the swirl flow and boosts concentration but serves to retard the tangential flow and decrease temperatures. With higher radiation contribution (lower Rc values) temperatures are elevated and concentrations are reduced. Verification of the MAPLE 17 solutions is achieved using a Keller-box finite difference method (KBM). A number of interesting features in the thermo-fluid and species diffusion characteristics are addressed. Key words: Stefan blowing; Spinning cone; MAPLE 17; Anisotropic
Report on my stay during March 2016 at the Yukawa Institute for Theoretical Physics

In this document I report my research outcome during my stay at the Yukawa Institute of Theoretical Physics from March 1 st and March 31 st , 2016, which is supported by the International Research Unit of Advanced Future Studies. The report mainly contains a non-technical summary of my recent study on effects of triangles in several network problems including percolation problem and neural network as associative memories.
Unsupervised Approach to Music Source Separation using Generalized Dirichlet Prior

Music source separation aims to extract and reconstruct individual instrument sounds that constitute a mixture sound. It has received a great deal of attention recently due to its importance in the audio signal processing. In addition to its stand-alone applications such as noise reduction and instrument-wise equalization, the source separation can directly affect the performance of the various music information retrieval algorithms when used as a pre-processing. However, conventional source separation algorithms have failed to show satisfactory performance especially without the aid of spatial or musical information about the target source. To deal with this problem, we have focused on the spectral and temporal characteristics of sounds that can be observed in the spectrogram. Spectrogram decomposition is a commonly used technique to exploit such characteristics; however, only a few simple characteristics such as sparsity were utilizable so far because most of the characteristics were difficult to be expressed in the form of algorithms. The main goal of this thesis is to investigate the possibility of using generalized Dirichlet prior to constrain spectral/temporal bases of the spectrogram decomposition algorithms. As the generalized Dirichlet prior is not only simple but also flexible in its usage, it enables us to utilize more characteristics in the spectrogram decomposition frameworks. From harmonicpercussive sound separation to harmonic instrument sound separation, we apply the generalized Dirichlet prior to various tasks and verify its flexible usage as well as fine performance.
Adaptive eigensystem truncation for spectral shape signatures

ABSTRACTThe ability to compare the shapes of objects is crucial to the practice of engineering design. Spectral shape signatures provide a high-quality similarity measure based on diffusion physics by means of the spectrum of an estimate of the Laplace-Beltrami operator for the surface of an object.However, point cloud and mesh models often have very large intrinsic sizes and subsequently large Laplace-Beltrami estimate matrices. Recommendations from the current spectral shape signature literature are to use only a fixed number of arithmetically greatest eigenvalues and their corresponding eigenvectors in the computation of a spectral shape signature. This recommendation “seems to work well”, but it is not yet understood the degree to which this fixed number of eigenpairs approximates the full spectrum for the purposes of shape similarity measures or even what fixed number to use. Using a fixed number of eigenpairs for all model sizes and samplings also introduces inconsistencies between different samplin.
The Construction and Practice of a TPACK Development Training Model for Novice University Teachers

The smart age has created new goals, and offers novel approaches for teachers’ professional development. The acquisition of technological pedagogical content knowledge (TPACK) has become essential for novice university teachers’ professional development. With the aim of developing teachers’ TPACK, this study constructed a BOPPPS–TPACK training model by following four key design principles: smart-tool-based, pedagogy-driven, microteaching-integrated, and creatively enhanced. This paper describes a practical study involving 145 teachers that was carried out using questionnaire surveys, interviews, and electronic record analyses. The results showed that the BOPPPS–TPACK training process could achieve the effective coupling of BOPPPS and TPACK and enhance novice university teachers’ ability to engage in in-depth learning and TPACK transfer, creating a method and system to guide teachers’ professional development. Measures such as optimizing the construction of smart environments for teachers’ professional development, enriching pedagogical content of knowledge-based representations, and extending feedback collection to practical settings can help to enhance TPACK development.
Immunization with a heat-killed prm1 deletion strain protects the host from Cryptococcus neoformans infection

ABSTRACT Systemic infection with Cryptococcus neoformans, a dangerous and contagious pathogen found throughout the world, frequently results in lethal cryptococcal pneumonia and meningoencephalitis, and no effective treatments and vaccination of cryptococcosis are available. Here, we describe Prm1, a novel regulator of C. neoformans virulence. C. neoformans prm1Δ cells exhibit extreme sensitivity to various environmental stress conditions. Furthermore, prm1Δ cells show deficiencies in the biosynthesis of chitosan and mannoprotein, which in turn result in impairment of cell wall integrity. Treatment of mice with heat-killed prm1Δ cells was found to facilitate the host immunological defence against infection with wild-type C. neoformans. Further investigation demonstrated that prm1Δ cells strongly promote pulmonary production of interferon-γ, leading to activation of macrophage M1 differentiation and inhibition of M2 polarization. Therefore, our findings suggest that C. neoformans Prm1 may be a viable target for the development of anti-cryptococcosis medications and, cells lacking Prm1 represent a promising candidate for a vaccine.
The Impact of COVID-19 Risk Perceptions on Travel Intention of Young Domestic Tourists in Kerala

The COVID-19 pandemic created a significant impact all over the world, specifically on the travel and tourism industry, which is an important economic contributor and highly sensitive to shocks like these pandemics. The impact of reduced mobility is highly reflected in the tourism industry, and countries across the world are trying to develop measures to ensure the recovery of the sector. So it is important to understand the attitude and perceptions of consumers to gain an insight into the change in travel intentions amidst the pandemic. The purpose of this study is to assess the impact of COVID-19 risk perceptions of young tourists in Kerala on travel intentions during the pandemic. Understanding the travel intentions in the current pandemic scenario is of paramount importance as strategies are needed to regain the confidence of tourists. This study has analysed the influence of financial risks, health risks, travel risks and psychological risks on travel intention, wherein health risks, travel risks and psychological risks were identified to influence travel intention. The health risk has influenced travel intentions, followed by travel risk and psychological risk.
A Novel Pathogen of an Emerging Infectious Disease (Large Kidney Disease) in Farmed Blue Foxes

An emerging infectious disease (EID) in foxes called “large kidney disease”, characterized by enlarged kidneys, has been breaking out in fox farms in China, although its pathogenesis has not yet been elucidated. Here, we performed viral metagenomics sequencing on diseased fox tissue samples that identified a virus with 82.6% homology to the xenotropic murine leukemia virus-related virus (XMRV) PreXMRV-1 provirus strain (GenBank accession number NC_007815.2) in sick fox tissue. It was named PreXMRV-20, and its genome was verified by reverse transcription-polymerase chain reaction (PCR) and PCR product sequencing. Nonenveloped and polygonal virus-like particles consistent with the shape and size of XMRV were observed by negative staining electron microscopy. Administered subcutaneously, PreXMRV-20 infected weaned foxes, leading to growth retardation. The discovery of the PreXMRV-20 strain (the first isolation of an XMRV homolog in blue foxes) identifies a potential public health issue in blue fox breeding since XMRV has been confirmed to be a zoonotic virus.
Integrated Digital Marketing Communication Strategy of Primago Islamic Boarding School in Building Netizen Cognitive

Digital transformation develops and disrupts the business sector and the economy. All Primago marketing communication activities are mediated digitally. The basic problem of this research is that Primago Digital's marketing communication activities need a model. This model is expected to deliver that effectiveness and efficiency in each Primago digital marketing communication program. The aims of this research are (1) to find the factors to be considered in designing an integrated digital marketing communication strategy for Primago. (2) To find priority choices in building netizen cognition. It is based on the multiple assessment criteria of experts. This study uses the theory of Computer-Mediated Communication, Information Integration Theory, and then the concept of Integrated Marketing Communications. For methodology, this study uses a post-positivism paradigm. The results of the interviews and dissemination of disclosures were then analyzed without the in-depth involvement of the researcher. Qualitative and quantitative methods are used simultaneously in this study. Based on the analysis of this study resulted in conclusions. (1) factors must be considered in designing Primago's digital marketing communication strategy. Among others are Accessible, Affordable, Connectivity, Costumize, and Real-Time Measurement. (2) The priority for choosing the right digital integrated marketing communication strategy for Primago in building netizen cognition sequentially is managing the website. Then simultaneously managing Facebook and Instagram, the third is YouTube and TikTok.
Students' Numeracy in Solving Problem of Counting Rules and Its Scaffolding

Numeracy is an ability that suits 21st-century skills. However, the result of PISA 2018 shows that the majority of Indonesian students still do not have good numeracy. The purpose of this research is to analyze students’ numeracy in solving problem of counting rules and to describe its scaffolding. The research method is descriptive qualitative. The research subjects were three students of XII-B SMA Plus Ar-Rahmat Bojonegoro who were given a written test and interview. The written test consists of one numeracy problem. The result indicates that students’ numeracy in solving problem of counting rules is not good yet. Students are able to correctly answer and comprehend problem after receiving scaffolding. Hence to improve students’ numeracy in solving problem of counting rules, a guide in the form of scaffolding is needed that is applied to each indicator of the numeracy process.
Reliability-Driven End–End–Edge Collaboration for Energy Minimization in Large-Scale Cyber-Physical Systems

In recent years, cyber-physical systems (CPS) have been widely deployed in industrial manufacturing fields and our daily living domains. End–end–edge collaboration, coupling mobile edge computing and device-to-device communication, is a promising computation paradigm to meet the stringent real-time demands of large-scale CPS applications. However, energy and reliability concerns should be carefully addressed in end–end–edge collaboration-empowered large-scale CPS due to the limited energy supply and inherent openness characteristic of end devices. In this article, we explore the reliability-driven energy optimization of end–end–edge collaborated large-scale CPS applications. We develop a reliability-driven end–end–edge collaboration approach to deal with the energy minimization problem. Our approach first designs a clustering method to quantify differentiated energy demands by analyzing the energy dissipation composition of heterogeneous applications. Afterward, our approach leverages incremental control and swarm intelligence-based techniques to obtain energy-efficient reliability-guaranteed task offloading solutions for differentiated application clusters. Experimental results reveal that our approach achieves 51.48% energy savings compared with peer algorithms.
The Spatially Distributed Neutron Activation Diagnostic FNADs at the National Ignition Facility

Abstract In need of a spatially resolved neutronic measurement to better understand the implosion physics of inertial-confined fusion, the National Ignition Facility (NIF) developed a distributed Flange-mounted Neutron Activation Diagnostic system (FNAD). FNAD measures primary deuterium-tritium (D-T) fusion neutron fluence at 20 points surrounding the target chamber using the 90Zr(n,2n)89Zr reaction, utilizing the 12.1-MeV reaction threshold to minimize signal from spurious neutron sources. Through careful design of the measurement systematics, the relative ratios of fluence at those 20 points are measured to within 2%. This precision is sufficient to allow interpretation of the resulting neutron sky as a map of scattering mass areal density (ρR) of the cold compressed D-T fuel surrounding the nuclear burn. Controlling the shape of this fuel during assembly is essential to achieving optimal implosion performance. This paper details the system design and locational deployment, measurement techniques, and calibration procedure. It also outlines data analysis and reduction, and data presentation methods used during the National Ignition Campaign and High-Foot Campaign.
Voltage Bias Scheme Optimization in FeFET Based Neural Network System

In this work, we focused on the performance optimization of the neural network (NN) system in the synaptic device of HfAlOx (HAO)-based ferroelectric field-transistors (FeFET), especially with the voltage bias scheme. The weights linearity, power consumption, and current ratio of the HAO-FeFET based synapse are measured under different voltage bias. Using the open-source tool “NeuroSim $^{\mathbf {+{''}}}$ , the training accuracy, and power efficiency can be evaluated. It shows that the performance of the NN is highly dependent on gate/drain’s voltages bias of the FeFETs. To suppress the nonlinearity of both the potentiation and depression during online training, the FeFET were biased at the triode and saturation region respectively under a large gate voltage bias. However, the power consumption will increase for inference, which should be a trade-off for system optimization.
Mannheim Peritonitis Index as a Predictor of Post-operative Complications, Mortality and Duration of Hospital Stay in Patients with Peritonitis due to Hollow Viscus Perforation: A Prospective Cohort Study

Introduction: Peritonitis due to hollow viscus perforation is a common surgical emergency and can be life-threatening. Patients who undergo surgery for peritonitis require extensive counselling to fully understand the nature of the disease, the need for surgery, post-operative complications and the duration of hospital stay. Hence, scoring systems are necessary to determine the severity of the disease to provide sufficient prognostic data. Aim: To evaluate the Mannheim Peritonitis Index (MPI) scoring system as a predictor of post-operative complications, mortality and duration of hospital stay in patients with peritonitis due to hollow viscus perforation. Materials and Methods: The prospective cohort study was carried out in 50 diagnosed cases of perforation peritonitis admitted at the centre during the study period from November 2017 to October 2018. MPI was calculated for each patient, following which they were stratified into three risk groups- 1, 2 and 3 with scores of ≤20, 21-29 and ≥30, respectively. Post- operative complications, mortality, and duration of hospital stay were analysed. Statistical analysis was done using the Statistical Package for the Social Sciences (SPSS) software 24.0. Results: Out of 50 patients included, 36 were male and 14 were female with a mean age of 41.14 years. A total of eight patients suffered mortality. The incidence of mortality in risk Group-1 was 0 out of 29 patients (0%), risk Group-2 was 3 out of 13 patients (23.1%) and risk Group-3 was 5 out of 8 patients (62.5%), respectively and hence MPI was a useful indicator of prediction of mortality in perforation peritonitis patients. The risk factors which had a higher significance in predicting mortality were found to be, organ failure at presentation and the nature of intra-peritoneal exudate with a p-value of 0.029 and <0.001, respectively. In 29 patients, there were no complications and 13 patients had a single complication, 8 patients had multiple complications. The incidence of multiple post-operative complications in a patient in risk Group-1, 2 and 3 were 1 (12.5%), 2 (25%) and 5 (62.5%) patients, respectively. The number of complications in a patient increased as the MPI score increases. Dispersion of duration of hospital stay in discharged patients according to MPI score using Pearsons’s correlation, showed statistical significance with the value of r being 0.6214, the p-value being 0.000011. The duration of hospital stay of patients who were discharged, increased as the MPI score increased. Conclusion: MPI was effective in predicting post-operative complications, mortality and duration of hospital stay in patients with peritonitis due to hollow viscus perforation and hence can be used as an effective tool to facilitate counseling and educate the patient and relatives regarding the expected course of the disease in that particular patient.
Wireless Vibration Signal Prediction of Power Transformers Based on Contrastive Adversarial Sparse Model

Wireless vibration analysis is regarded as a cost-effective and nondestructive method for monitoring the operational states of power transformers. However, influenced by noise and mutation information, vibration-based prediction methods remain in the preliminary phase for precise prediction of power transformer. To address this issue, a contrastive adversarial sparse model is proposed to predict the progress of power transformer faults in the early phases. First, a sparse transformer improves the feature extraction ability of the bidirectional recurrent gated network to reduce noise and extracts significant information from original signal. Then, the mutation information is suppressed by a contrastive adversarial method, based on which discrimination layer predicts the power transformer fault. Finally, to constrain the network, a contrastive loss based on feature matching is proposed to learn more extra information distinct from sparse transforms. Datasets are collected using wireless vibration sensors from a 10-kV real power transformer. Under an identical parameter setting, experimental results show that the proposed model outperforms comparison algorithms in terms of root mean square error (RMSE), correlation coefficient, symmetric mean absolute percentage error, and mean absolute error. Especially, the RMSE of the proposed model is 0.0242, exceeding the performance of the conventional model in power transformer fault prediction.
Identification and quantitative assessment of motor complications in Parkinson’s disease using the Parkinson’s KinetiGraph™

Introduction Effective management and therapies for the motor complications of Parkinson’s disease (PD) require appropriate clinical evaluation. The Parkinson’s KinetiGraph™ (PKG) is a wearable biosensor system that can record the motion characteristics of PD objectively and remotely. Objective The study aims to investigate the value of PKG in identifying and quantitatively assessing motor complications including motor fluctuations and dyskinesia in the Chinese PD population, as well as the correlation with the clinical scale assessments. Methods Eighty-four subjects with PD were recruited and continuously wore the PKG for 7 days. Reports with 7-day output data were provided by the manufacturer, including the fluctuation scores (FS) and dyskinesia scores (DKS). Specialists in movement disorders used the Movement Disorder Society-Unified Parkinson’s Disease Rating Scale-IV (MDS-UPDRS IV), the wearing-off questionnaire 9 (WOQ-9), and the unified dyskinesia rating scale (UDysRS) for the clinical assessment of motor complications. Spearman correlation analyses were used to evaluate the correlation between the FS and DKS recorded by the PKG and the clinical scale assessment results. Receiver operating characteristic (ROC) curves were generated to analyze the sensitivity and specificity of the FS and DKS scores in the identification of PD motor complications. Results The FS was significantly positively correlated with the MDS-UPDRS IV motor fluctuation (items 4.3–4.5) scores (r = 0.645, p < 0.001). ROC curve analysis showed a maximum FS cut-off value of 7.5 to identify motor fluctuation, with a sensitivity of 74.3% and specificity of 87.8%. The DKS was significantly positively correlated with the UDysRS total score (r = 0.629, p < 0.001) and the UDysRS III score (r = 0.634, p < 0.001). ROC curve analysis showed that the maximum DKS cut-off value for the diagnosis of dyskinesia was 0.7, with a sensitivity of 83.3% and a specificity of 83.3%. Conclusion The PKG assessment of motor complications in the PD population analyzed in this study has a significant correlation with the clinical scale assessment, high sensitivity, and high specificity. Compared with clinical evaluations, PKG can objectively, quantitatively, and remotely identify and assess motor complications in PD, providing a good objective recording for managing motor complications.