Miracle-dz/UniFAR-FTUs huggingface dataset:
Transport of Entropy Waves Within a High Pressure Turbine Stage

This paper presents the results of an experimental study on the transport of entropy waves within a research turbine stage, representative of the key aero-thermal phenomenon featuring the combustor-turbine interaction in aero-engines. The entropy waves are injected upstream of the turbine by a dedicated entropy wave generator (EWG) and are released in axial direction; they feature circular shape with peak amplitude in the center and exhibit sinusoidal-like temporal evolution over the whole wave area. The maximum over-temperature amounts to 7% of the undisturbed flow, while the frequency is 30 Hz. The entropy waves are released in four azimuthal positions upstream of the stage, so to simulate four different burner-to-stator blade clocking. Time-resolved temperature measurements were performed with fast microthermocouples (FTC); the flow and the pressure field upstream and downstream of the stator and the rotor was measured with five-hole pneumatic probes and fast-response aerodynamic pressure probes. The entropy waves are observed to undergo a relevant attenuation throughout their transport within the stator blade row, but they remain clearly visible at the stator exit and retain their dynamic characteristics. In particular, the total temperature distribution appears severely altered by burner-stator clocking position. At the stage exit, the entropy waves loose their coherence, appearing spread in the azimuthal direction to almost cover the entire pitch in the outer part of the channel, while being more localized below midspan. Despite the severe and unsteady interaction of the entropy waves within the rotor, they retain their original dynamic character. A comparison with measurements performed by injecting steady hot streaks is finally reported, remarking both differences and affinities. As a relevant conclusion, it is experimentally shown that entropy waves can be proficiently simulated by considering a succession of hot streaks of different amplitude.
FINITE TYPE MINIMAL ANNULI IN S 2 × R

We study minimal annuli in S2 × R of finite type by relating them to harmonic maps C ! S2 of finite type. We rephrase an iteration by Pinkall-Sterling in terms of polynomial Killing fields. We discuss spectral curves, spectral data and the geometry of the isospectral set. We consider polynomial Killing fields with zeroes and the corresponding singular spectral curves, bubbletons and simple factors. We investigate the differentiable structure on the isospectral set of any finite type minimal annulus. We apply the theory to a 2-parameter family of embedded minimal annuli foliated by horizontal circles.
An Implementable SAA Nonlinear Lagrange Algorithm for Constrained Minimax Stochastic Optimization Problems

This paper proposes an implementable SAA (sample average approximation) nonlinear Lagrange algorithm for the constrained minimax stochastic optimization problem based on the sample average approximation method. A computable nonlinear Lagrange function with sample average approximation functions of original functions is minimized and the Lagrange multiplier is updated based on the sample average approximation functions of original functions in the algorithm. And it is shown that the solution sequences obtained by the novel algorithm for solving subproblem converge to their true counterparts with probability one as the sample size approximates infinity under some moderate assumptions. Finally, numerical experiments are carried out for solving some typical test problems and the obtained numerical results preliminarily demonstrate that the proposed algorithm is promising.
Mathematical Modelling of Effects of Non-Clinical Strategies in Combating Transmission of SARS-CoV-2 in Kenya

SARS-CoV-2 is a serious problem in Kenya today. It has put an unprecedented burden on worldwide economy and public health. The rapid spread of SARS-CoV-2 has been driven predominantly by aerosol transmissions. The objectives of this study were to formulate mathematical models on the spread of SARS –CoV-2 and incorporating the effects of nonclinical strategies like screening, facemask usage, hand washing and social distancing, determine well posedness of the model, validate the developed model and finally predict the effects of nonclinical strategies on the dynamics of the spread of SARS-CoV-2 in Kenya. The mathematical model was based on SIRS epidemiological classical model. In developing the model, the population was divided into six human compartments; susceptible, exposed, infected, isolated in hospital, at home and recovered. The basic reproduction number was determined using next generation method. The model was analyzed through the determination of the model steady states. The stabilities of steady states analyzed based on reproduction number (R0) using: signs of Jacobi matrix evaluated at steady state, Lyapnov criteria, centre manifold theorem, Metzler matrix and Routh-Hurwitz. Numerical simulations were carried out using MATLAB inbuilt ode solver based on Runge Kutta method. Sensitivity analysis of the model parameters was carried out using partial differentiation of the reproduction number and also using normalized sensitivity analysis. From this analysis, findings showed that adherence to the containment measures and contact tracing had the greatest negative impact on the reproduction number. It was found through simulation that adherence to the SARS-CoV-2 containment measures by the population would reduce the reproduction number to below 1 hence containing the pandemic. The findings of this study show the extent to which the nonclinical can be used to contain the spread of SARS-CoV-2in Kenya. We recommended strict adherence to containment
Weighted Risk Minimization & Deep Learning

Importance weighting is a key ingredient in many algorithms for causal inference and related problems, such as off-policy evaluation for reinforcement learning. Recently, theorists proved that on separable data, unregularized linear networks, trained with cross-entropy loss and optimized by stochastic gradient descent converge in direction to the max margin solution. This solution depends on the location of data points but not their weights, nullifying the effect of importance weighting. This paper asks, for realistic deep networks, for which all datasets are separable, what is the effect of importance weighting? Lacking theoretical tools for analyzing modern deep (nonlinear, unregularized) networks, we investigate the question empirically on both realistic and synthetic data. Our results demonstrate that while importance weighting alters the learned model early in training, its effect diminishes to negligible with indefinite training. However, this diminishing effect does not occur in the presence of L2-regularization. These results (i) support the broader applicability of theoretical findings by Soudry et al (2018), who analyze linear networks; (ii) call into question the practice of importance weighting; and (iii) suggest that its usefulness interacts strongly with the early stopping criteria and regularization methods that interact with the loss function.
Cancer cases managed by synergistic therapy

Two cases of obstinate cancers are cured by a new hypothesis of synergistic therapy approach where Cancer Homoeotherapeutics were analysed scientifically by immunotherapy where modus operandi of homoeopathic medicine selection is done by activating natural cancer immunity by natural killer cells (NK) through the interferon produced by viral infection. So synthesis of antiviral medicine and antimiasmatic medicine is done to treat cancer cases.
Penerapan Metode Resampling dan K-Nearest Neighbor dalam Memprediksi Keberhasilan Studi Mahasiswa Program Magister IPB

Graduate School IPB (SPs - IPB) has been established for a long time and is believed to produce high quality graduates and highly competitive. However, based on existing data recaps, there are a small number of students who did not graduate, either resigned or Drop Out (DO). It needs to be handled by conducting a selection process for prospective students based on the profile and educational background S1. One of them by applying the method of classification K - Nearest Neighbor (KNN). The response variable used is the success status of the study of prospective students, ie graduated and not graduated. While the explanatory variables used are the profiles and educational background of prospective students. There is an imbalance of data in the data obtained, where the class does not pass much less than the passing class. This can reduce the value of classification accuracy in minority class (sensitivity). So that the handling of data imbalance by using resampling method, either in the form of Random Over Sampling (ROS), Random Under Sampling (RUS), and Random Over-Under Sampling (ROUS). The result of comparison of evaluation result of KNN classification by using k = 1 to 6, resulted in greater sensitivity value when accompanied by the process of handling the data imbalance than without the process of handling the data imbalance, although the accuracy and specificity value becomes smaller. The greatest sensitivity value was obtained when applying the KNN classification method with k = 1, accompanied by the handling of data imbalance by the RUS method, with the mean and median sensitivity values of 0.89 and 0.90, respectively.
REGULAR MILDLY GENERALIZED CLOSED AND REGULAR MILDLY GENERALIZED OPEN MAPS IN TOPOLOGICAL SPACES.

The aim of this paper is to introduced the concept of (τi, τj)-Regular Mildly Generalized (briefly (τi, τj)RMG) closed and (τi, τj)-Regular Mildly Generalized (briefly (τi, τj)-RMG) open sets and study their basic properties in bitopological spaces. Further we define and study new neighborhood namely (τi, τj)Regular Mildly Generalized (briefly (τi, τj)-RMG-nhd), (τi, τj)-Regular Mildly Generalized (briefly (τi, τj)-RMG-closure) closure and (τi, τj)-Regular Mildly Generalized (briefly (τi, τj)-RMG-interior) interior and discuss some of their properties in bitopological spaces. Also give some characterizations and applications of it. Mathematics Subject Classification 2010: 54C08, 54C010, 54C20
An Ant Colony Optimization algorithm for solving the fixed destination multi-depot multiple traveling salesman problem with non-random parameters

The Multiple Traveling Salesman Problem (MTSP) is the extension of the Traveling Salesman Problem (TSP) in which the shortest routes of m salesmen all of which start and finish in a single city (depot) will be determined. If there is more than one depot and salesmen start from and return to the same depot, then the problem is called Fixed Destination Multi-depot Multiple Traveling Salesman Problem (MMTSP). In this paper, MMTSP will be solved using the Ant Colony Optimization (ACO) algorithm. ACO is a metaheuristic optimization algorithm which is derived from the behavior of ants in finding the shortest route(s) from the anthill to a form of nourishment. In solving the MMTSP, the algorithm is observed with respect to different chosen cities as depots and non-randomly three parameters of MMTSP: m, K, L, those represents the number of salesmen, the fewest cities that must be visited by a salesman, and the most number of cities that can be visited by a salesman, respectively. The implementation is observed wi.
Conditional Dynamics and the Multi-Horizon Risk-Return Trade-Off

We propose testing asset pricing models using multihorizon returns (MHRs). MHRs effectively generate a new set of test assets that is endogenous to the model and that identifies a broad set of possible conditional misspecifications. We apply MHR-based testing to prominent linear factor models and show that these models typically do a poor job of pricing longer-horizon returns, with pricing errors that are similar in magnitude to the risk premiums they were designed to explain. We trace the errors to the conditional factor dynamics. Explicitly incorporating factor timing into the models often makes mispricing worse, thereby posing a challenge for future research.
Factor Affecting Customer Satisfaction of Mobile Banking Services of Commercial Bank in Kathmandu Valley

Mobile banking has achieved a great importance in Nepal's banking sector. Though majority of Nepalese banks have recognized the importance of understanding customer psychology and are highly conscious of it. some banks often struggle to keep pace with customer expectations. This paper specifically targets commercial bank customers and aims to uncover their differential perceptions. The study aims to identify the most influential factors that affect customer satisfaction and retention in mobile banking and determine their relative impact. The Exploratory research design was adopted as the main research paradigm to discover the reality. The data was evaluated quantitatively by using both descriptive and inferential statistics. Convenience sampling has used data collection and Structural Equation Modeling (SEM) was used to analyze the relationships from 403 responses. The research findings indicated that security, responsiveness, and convenience have a significant impact on customer satisfaction, while cost and relative advantage have a negligible impact. However, although customer satisfaction and loyalty are strongly related, these factors are not directly related to loyalty. This finding holds theoretical relevance for the Service Quality Theory. The scope and depth of this study is limited to banking customers of Kathmandu Valley. Further studies should include other variables to better understand the underlying relationship between customer satisfaction. Implication includes researchers, banking authority and policy makers who focus on enhancing mobile banking services. Mobile banking is an essential aspect that demands greater priority. Significant enhancements must be made to strengthen security measures, ensure stable service and support, and establish a fairly structured cost system to ensure better modern banking and financial systems.
Sampling of the Wiener Process for Remote Estimation Over a Channel With Random Delay

In this paper, we consider a problem of sampling a Wiener process, with samples forwarded to a remote estimator over a channel that is modeled as a queue. The estimator reconstructs an estimate of the real-time signal value from causally received samples. We study the optimal online sampling strategy that minimizes the mean square estimation error subject to a sampling rate constraint. We prove that the optimal sampling strategy is a threshold policy, and find the optimal threshold. This threshold is determined by how much the Wiener process varies during the random service time and the maximum allowed sampling rate. Further, if the sampling times are independent of the observed Wiener process, the above sampling problem for minimizing the estimation error is equivalent to a sampling problem for minimizing the age of information. This reveals an interesting connection between the age of information and remote estimation error. Our comparisons show that the estimation error achieved by the optimal sampling policy can be much smaller than those of age-optimal sampling, zero-wait sampling, and periodic sampling.
Accounting Treatment of Drilling and Development Expenses Between the International Reporting Standard Ifrs 6 and the Unified Accounting System (A Comparative Study)

Purpose: The purpose of this research is to identify the accounting treatments for drilling and development expenses in the Iraqi oil companies according to the unified accounting system, and to indicate the extent of compatibility and difference in the treatment of drilling and development expenses between the unified accounting system and the International Financial Reporting Standard IFRS 6. Theoretical framework: The oil industry includes many activities and operations, starting from research and exploration operations through drilling and development operations, and ending with extracting oil from the well and delivering it to the consumer or transferring it to the refining industry. During these activities expenses are realized that should be accounted for in a way that ensures compliance with international standards for the oil industry as Iraq particularly witness a great development in the oil industry represented in dealing with foreign oil investment companies which means the need to standardize accounting treatments for the oil industry between local oil companies and foreign oil companies. Design/methodology/approach: The research used comparative descriptive approach by comparing the accounting treatment of drilling and development expenses under the International Financial Reporting Standard IFRS 6 and the unified accounting system applied in Iraq represented by the Basra Oil Company and the Iraqi Drilling Company. Findings: One of the most important findings of the research is the concord of the method used by the Basra Oil Company in capitalizing drilling expenses at the expense of wells under operation with the philosophy of the total cost method approved by the standard. However, this agreement is conditional on the absence of dry wells. If the drilling operations resulted in the presence of non-productive or productive wells but in uneconomical quantities, the treatment becomes not compatible with the standard. The practical and social implications: The Basra Oil Company treats all development (maintenance) expenses as operating expenses that are closed at the end of the year in the income statement, this it is not consistent with the philosophy of Standard No. 6 which states that development expenses that aim to maintain the production capacity of the well should be treated as operating expenses, but if development expenses that aim to increase the production capacity of the well must be capitalized on the cost of the well. Originality/ Value: The importance of the research comes from the need to work on applying the requirements of the International Financial Reporting Standard IFRS 6 in accounting treatments for oil expenditures, including drilling and development expenses in Iraqi oil companies.
Diurnal Cycle of a Heavy Rainfall Corridor over East Asia

AbstractMoist convection occurred repeatedly in the midnight-to-morning hours of 11–16 June 1998 and yielded excessive rainfall in a narrow latitudinal corridor over East Asia, causing severe flood. Numerical experiments and composite analyses of a 5-day period are performed to examine the mechanisms governing nocturnal convection. Both simulations and observations show that a train of MCSs concurrently developed along a quasi-stationary mei-yu front and coincided with the impact of a monsoon surge on a frontogenetic zone at night. This process was regulated primarily by a nocturnal low-level jet (NLLJ) in the southwesterly monsoon that formed over southern China and extended to central China. In particular, the NLLJ acted as a mechanism of moisture transport over the plains. At its northern terminus, the NLLJ led to a zonal band of elevated conditionally unstable air where strong low-level ascent overcame small convective inhibition, triggering new convection in three preferred plains. An analysis of con.
Short term outcome of arthroscopic single bundle ACL reconstruction using quadruple hamstring graft by transportal technique for complete ACL tear

Objective: To study short term outcome of arthroscopic single bundle ACL reconstruction using quadruple hamstring graft by transportal technique. Introduction: Arthroscopic ACL reconstruction is the ‘Gold Standard’ treatment for ACL tear. 70% of ACL injuries occur through non-contact mechanisms. The goal of surgery is to prevent instability & restore the functions of torn ligament & creating a stable knee. Various grafts are used but quadruple hamstring graft has excellent material strength with excellent functional outcomes. Methodology: A cohort of 20 complete ACL tear, treated with arthroscopic single bundle ACL reconstruction using quadruple hamstring graft by transportal technique between Sep 2015 and Sep 2016 were analyzed at minimum 3months follow up. Results: 20 out of 20 patients had excellent result. Assessment was done using “Modified Cincinnati Scoring System”. No major complication were noted.
On stability of discrete-time quantum filters

Fidelity is known to increase through a Kraus map: the fidelity between two density matrices is less than the fidelity between their images via a Kraus map. We prove here that, in average, the square of the fidelity is also increasing for a quantum filter: the square of the fidelity between the density matrix of the underlying Markov chain and the density matrix of its associated quantum filter is a super-martingale. Thus discrete-time quantum filters are stable processes and tend to forget their initial conditions. 1K raus maps and quantum Markov chains Take the Hilbert space S = C n of dimension n> 0 and consider a quantum channel
Profiles of problematic social networking site use: A cross-cultural validation of a scale with Spanish and Mexican adolescents

In recent years, increasing interest in social networking site (SNS) use has resulted in a large body of research examining addiction to SNSs. The aim of this study was to cross-culturally validate a Spanish adaptation of the Problematic Social Networking Site Use Scale (PSNUS) based on the General Problematic Internet Use Scale (GPIUS-2) and to stablish profiles by using latent profile analysis (LPA) to compare the proportion of problematic use between Spanish and Mexican adolescents. The sample was composed of 1,534 Spanish and Mexican students (55.0% girls) 15–17 years of age. Confirmatory factor analysis and the invariance of the PSNUS were examined; the scale displayed good structural validity and achieved full metric invariance. The PSNUS demonstrated good reliability indexes, convergent, discriminant, and criterion validity with respect to the number of days the participants used an SNS, the duration of use, and GPIUS-2 dimension scores. LPA based on the five PSNUS dimensions revealed the existence of five profiles: among them, a clear non-problematic user group that comprised 44.6%; an at-risk group that comprised 13.2% of the sample; and a clear problematic user profile making up 2.9% of the sample. This study provides validation of the PSNUS for two Spanish-speaking countries; it may be used as an alternative to the prevailing component model of addiction to SNS use.
AddAG-AE: Anomaly Detection in Dynamic Attributed Graph Based on Graph Attention Network and LSTM Autoencoder

Recently, anomaly detection in dynamic networks has received increased attention due to massive network-structured data arising in many fields, such as network security, intelligent transportation systems, and computational biology. However, many existing methods in this area fail to fully leverage all available information from dynamic networks. Additionally, most of these methods are supervised or semi-supervised algorithms that require labeled data, which may not always be feasible in real-world scenarios. In this paper, we propose AddAG-AE, a general dynamic graph anomaly-detection framework that can fuse node attributes and spatiotemporal information to detect anomalies in an unsupervised manner. The framework consists of two main components. The first component is a feature extractor composed of a dual autoencoder, which captures a joint representation of both the network structure and node attributes in a latent space. The second component is an anomaly detector that combines a Long Short-Term Memory AutoEncoder (LSTM-AE) and a predictor, effectively identifying abnormal snapshots among most normal graph snapshots. Compared with baselines, experimental results show that the method proposed has broad applicability and higher robustness on three datasets with different sparsity.