Miracle-dz/UniFAR-FTUs huggingface dataset:
Integrated Extensive Detection, Contact Tracing and Dynamical Social Distancing Interventions to Prevent Future Epidemic Waves

In the absence of sufficient vaccination and rapid mutation of the virus, joint interventions of detection, contact tracing and social distancing are considered to be key strategies in suppressing emergent epidemics. Here, we propose the susceptible-exposed-infected-quarantined-recovered (SEIQR) model with detection, contact tracing, and dynamical social distancing to quantify the effectiveness of joint interventions. Under the framework of time-varying networks, we analytically derive the epidemic threshold and the effective reproductive number under joint interventions by using the mean-field approach. Experimental results show that detection and contact tracing can significantly reduce the epidemic scale, while social distancing can remarkably delay the peak time and suppress the second outbreak of the epidemic. Compared with constant social distancing, the effectiveness of dynamical social distancing depends on the starting time and the intervention period, and extensive detection can greatly reduce its dependence on them. Further, we explore the effects of heterogeneous distributions of physical distance and contact duration on the effectiveness of joint interventions in high-resolution empirical contact networks. We find that extensive contact tracing is more effective in decreasing the “false negatives,” but at the expense of unnecessary large-scale quarantines of the “false positives. ” Meanwhile, the early implementation of long-term social distancing can effectively reduce the “false negatives” and “false positives. ” In conclusion, it is very important to ensure extensive detection and contact tracing, while maintaining moderate social distancing to suppress the epidemic spread and prevent epidemic recurrence.
Enhancing sampling in computational statistics using modified hamiltonians

The Hamiltonian Monte Carlo (HMC) method has been recognized as a powerful sampling tool in computational statistics. In this thesis,we showthat performance ofHMCcan be dramatically improved by replacing Hamiltonians in theMetropolis test with modified Hamiltonians, and a complete momentum update with a partial momentum refreshment. The resulting generalized HMC importance sampler, whichwe called Mix & Match Hamiltonian Monte Carlo (MMHMC), arose as an extension of the Generalized Shadow Hybrid Monte Carlo (GSHMC) method, previously proposed for molecular simulation. The MMHMC method adapts GSHMC specifically to computational statistics and enriches it with new essential features: (i) the e icient algorithms for computation of modified Hamiltonians; (ii) the implicit momentum update procedure and (iii) the two-stage splitting integration schemes specially derived for the methods sampling with modified Hamiltonians. In addition, di erent optional strategies formomentumupdate and flipping are introduced as well as algorithms for adaptive tuning of parameters and e icient sampling of multimodal distributions are developed. MMHMChas been implemented in the in-house so ware package HaiCS (Hamiltonians in Computational Statistics) written in C, tested on the popular statistical models and compared in sampling e iciency with HMC, Generalized Hybrid Monte Carlo, Riemann Manifold Hamiltonian Monte Carlo, Metropolis Adjusted Langevin Algorithm and RandomWalk Metropolis-Hastings. The analysis of time-normalized e ective sample size reveals the superiority of MMHMC over popular sampling techniques, especially in solving high-dimensional problems.
Human Resource Accounting Toward Human Welfare

Objective: The debate on human resource accounting is still ongoing, namely in particular the accounting treatment on the recognition of all human resource expenditures, whether recognized as an expense or an asset. As the company’s driving force, humans have an important role but are recognized as an expense in the financial statements. Therefore, this study aimed to develop an alternative model in human resource accounting.Design: This study was structured to build a human resource accounting model by synthesizing the biological asset concept in recognition and measurement. It also used Homo religious analysis to clarify the nature and treatment of human resource accounting.Finding: The concept of human resource accounting was compiled through the growth, production, degeneration, and procreation cycle. Human resource accounting based on homo economicus is far from human values. It only touches on material but not other aspects of human welfare. Additionally, the value was added by synthesizing homo religious as a model for developing human resource accounting. This value complements the position of human resource accounting to cover the aporetic problems between humans, accounting, and God.Theoretical and practical implications: First, human resource accounting is structured based on its characteristics, recognition, and measurement through several stages. This is expected to explain the position of human resources as a burden or an asset. Furthermore, the structuring should have a materialistic economic motive and must be based on God's law in achieving human welfare. Second, it is important to treat human resources by aligning the soul, nature, and God as a manifestation of added value. This aims to balance human resources and the company and be reported in financial statements narratively.Originality: This study referred to the post-secular religious currents to contribute to critical and interdisciplinary awareness in accounting. It aimed to complete human resource accounting development by tracing humans as homo religious.
Two-Phase Positioning System Based on the Fusion of Wi-Fi Signal Strength and Pose Estimation

Due to the growing importance of positioning in recent years, global positioning system has become widely used. However, indoor positioning presents significant challenges due to multipath interference, which can cause large signal fluctuations and high positioning errors for signal-based approaches. Recent advances in deep learning have enabled researchers to estimate people's positions and locate them indoors using image recognition technology, but identification of individuals remains challenging. Therefore, we propose a highly accurate indoor positioning approach using Wi-Fi signals and images. This research employs smartphones to measure the signal strength of three Wi-Fi base stations' 2.4 and 5 GHz frequency bands. We then use machine learning techniques to estimate individuals' positions with coarse accuracy. Subsequently, we analyze the positions of individuals in surveillance camera images. We use OpenPose, an open-source multiperson pose estimation system, and propose a foot position extraction algorithm to extract the foot positions of individuals in the image. We obtain the coordinates of the people in the image through direct linear transformation and machine learning. Finally, we match the coordinates obtained from the two techniques to identify the user's device. Experimental results show that the proposed method achieves higher accuracy, with an average error of 0.43 meters.
Appraising the Availability, Accessibility, and Efficacy of Interactive Whiteboard for Instruction Amongst Lecturers in Public Tertiary Institutions in Sokoto State, Nigeria

: The world is stirring faster into technological innovations. One can say teaching and learning to our everchanging from traditional/conventional classroom situations to electronic classrooms. There are many things one can see and say this classroom is an electronic classroom; the use of web 2.0 tools, video conferencing, google classroom, the use of social networks to impart knowledge and skills, and the use of an interactive whiteboard. This research on “appraising the availability, accessibility
Towards the Development of Indicators of Fake Websites for Digital Investigation

A fake website is considered a website that is intended to cause harm and manipulate users, especially novice users without some knowledge of indicators of fakeness. Understanding the indicators of fake websites is thus considered an important concept to avoid being a victim of malicious attacks in online engagements. In some cases, such knowledge is required to reduce the potential attack surface of cyber criminals. However, the increasing rate of website diversity and complexities makes it difficult for an individual to distinguish between a fake and a real website while compounding the investigation process of a website. Also, the growing rate of website imitation technology and website domain closure presents a veritable platform for the development of fake websites. As a step towards determining the genuineness of a website, this study developed a forensic framework based on an exploratory analysis of different genres of fake websites. To achieve this, forensic methodologies and processes were applied to methodically selected samples of known fake websites based on three fakeness categories: Hoaxes, Cybersquatting, and Sweepstakes. The result revealed the existence of salient markers which can be used as indicators of fakeness and can be applied across a wide genre of websites. Furthermore, the resultant observation was used to develop a digital forensic framework for website fakeness evaluation. The developed framework was benchmarked to the ISO 27043/2015 and the NIST SP800-86 standard for completeness and relevance to forensic investigation processes. By leveraging the proposed digital forensic framework, an investigation can develop a reliable pointer to evaluate the genuineness of any website, which can significantly reduce the investigation time. For a non-forensic individual, the developed framework can be leveraged to identify, at first glance, the degree of fakeness of a website. Such a mechanism can therefore provide a useful tool to reduce the potential susceptibility of users thereby creating user awareness.
Measurement and Estimation of Cross Sections for 55Mn(n, γ)56Mn and 65Cu(n, γ)66Cu Reactions Using Accelerator-Based Neutron Source

Abstract The reaction cross sections of 55Mn(n, γ)56Mn and 65Cu(n, γ)66Cu have been measured over a neutron energy range from 1 keV to 4 MeV. The racetrack microtron accelerator-based neutron source was used for the cross-section measurement, which generates a neutron spectrum from 1 keV to 4 MeV. Moreover, the cross-sections of the nuclear reaction were calculated using TALYS-1.2 and EMPIRE nuclear codes. It has been observed that the experimental cross sections of manganese and copper are 8.5 mb and 4.5 mb, respectively, and they are quite close to the TALYS, EMPIRE, and evaluated data of ENDF/B-VII.0, ENDF/B-VII.1, JEFF-3.1.2, and EXFOR. For (n, γ) reactions studied in the present work, the results obtained using TALYS and EMPIRE codes are in agreement with literature values when the radiative capture width Гγ and the width fluctuation parameter, respectively, functioned by being adjusted to a suitable value. Further, the deviation factor for measured and theoretical cross sections has also been determined and it is found to be better for the 55Mn(n, γ)56Mn reaction obtained using TALYS compared to EMPIRE.
Estimating Sobol' indices combining Monte Carlo estimators and Latin hypercube sampling

In variance-based sensitivity analysis, the method of Sobol' (1993) allows to compute Sobol' indices using Monte Carlo integration. One of the main drawbacks of this approach is that the estimation of Sobol' indices requires the use of several samples. For example, in a d-dimensional space, the estimation of all the first-order Sobol' indices requires d+1 samples. Some interesting combinatorial results have been introduced to weaken this defect, in particular by Saltelli (2002) and more recently by Owen (2012) but the quantities they estimate still require O(d) samples. In this paper, we introduce a new approach to estimate for any k all the k-th order Sobol' indices by using only two samples. We establish theoretical properties of such a method for the first-order Sobol' indices and discuss the generalization to higher-order indices. As an illustration, we propose to apply this new approach to a marine ecosystem model of the Ligurian sea (northwestern Mediterranean) in order to study the relative importance of its several parameters. The calibration process of this kind of chemical simulators is well-known to be quite intricate, and a rigorous and robust --- i.e. valid without strong regularity assumptions --- sensitivity analysis, as the method of Sobol' provides, could be of great help.
On the approximate solutions of fragmentation equations

A numerical model based on the finite volume scheme is proposed to approximate the binary breakage problems. Initially, it is considered that the particle fragments are characterized by a single property, i.e. particle’s volume. We then investigate the extension of the proposed model for solving breakage problems considering two properties of particles. The efficiency to estimate the different moments with good accuracy and simple extension for multi-variable problems are the key features of the proposed method. Moreover, the mathematical convergence analysis is performed for one-dimensional problems. All mathematical findings and numerical results are validated over several test problems. For numerical validation, we propose the extension of Bourgade & Filbet (2008 Math. Comput. 77, 851–882. (doi:10.1090/S0025-5718-07-02054-6)) model for solving two-dimensional pure breakage problems. In this aspect, numerical treatment of the two-dimensional binary breakage models using finite volume methods can be treated to be the first instance in the literature.
E-Cloud Dependence on the Longitudinal Bunch Profile in the PS and the HL-LHC

During the HL-LHC era [1] the bunch intensities in the LHC will go up by nearly a factor of two compared to the LHC-design values [2]. However, recent studies have shown that the prospects for significantly increasing bunch intensities in the LHC may be severely limited by the electron-cloud (EC) driven beam instability and the available cryogenic cooling capacity. This motivates exploration of additional EC mitigation techniques that can be adopted along with those already in place. Preliminary simulations indicated that “flat” bunches can be beneficial over Gaussian bunches to reduce the EC build up. Rigorous studies on realistic bunch profiles have never been carried out. Therefore, we have undertaken an in-depth investigation in the CERN PS via EC-simulations and beam experiments to see if we can validate the previous findings and, in particular, if flattening the bunch can be used as a potential EC mitigation technique. Finally, we perform an extrapolation to the HL-LHC scenarios.
An Independent Asteroseismic Analysis of the Fundamental Parameters and Internal Structure of the Solar-like Oscillator KIC 6225718

Asteroseismology is a useful tool that is usually used to probe stellar interiors and to determine stellar fundamental parameters, such as stellar mass, radius, and surface gravity. In order to probe stellar interiors, making comparisons between observations and models is usually used with the χ 2 -minimization method. The work of Wu & Li reported that the best parameter determined by the χ 2 -matching process is the acoustic radius for pure p-mode oscillations. In the present work, based on the theoretical calculations of Wu & Li, we will independently analyze the seismic observations of KIC 6225718 to determine its fundamental parameters and to investigate its interior properties. First, in order to test the method, we use it in the Sun to determine its fundamental parameters and to investigate interiors. Second, we independently determine the fundamental parameters of KIC 6225718 without any other non-seismic constraint. Therefore, those determined fundamental parameters are independent of those determined by other methods. They can be regarded as independent references in other analyses. Finally, we analyze the stellar internal structure and find that KIC 6225718 has a convective core with the size of 0.078–0.092 R ☉ . Its overshooting parameter f ov in the core is around 0.010. In addition, its center hydrogen X c is about 0.264–0.355.
Implications of urban farming on urban resilience in Indonesia: Systematic literature review and research identification

Abstract This systematic literature review study aims to identify, review, and study the trend of scientific publications on urban farming in realizing the resilience of developing cities in Indonesia. The urban farming trend in Indonesia is a response to overcoming the problem of food security in urban areas as well as a solution to boosting the economy during the crisis due to COVID-19 and creating urban resilience. It will also explore the issue of urban farming as a supplier of projected food availability and food security in urban areas in Indonesia. This research provides scientific guidelines and recommendations for developing urban agriculture studies in Indonesia. This research can be used as scientific data and policy notes on the problem of urban farming in Indonesia. The findings of this study suggest that urban farming will help promote urban resilience in Indonesia, especially given the problems of production, food security, and land scarcity in urban areas. Urban farming in Indonesia’s urban resilience design has several weaknesses even though it has positive effects.
Pressure Mapping With Piezoresistive Sensor on Oxide TFTs Backplane

We report a pixel circuit with a piezoresistive sensor using amorphous indium-gallium-zinc oxide (a-IGZO) thin-film transistor (TFT) backplane for large-area pressure mapping. The proposed pixel circuit consists of TFTs, piezoresistive sensor, and a capacitor. The pressure sensor shows a large resistance change between 1011 and 107 ohm. The RC charging time to the capacitance can be modulated by pressure-dependent resistance within pre-charging period for sensing. The pressure sensor array has a resolution of 0.625 mm, rising and falling times of <inline-formula> <tex-math notation="LaTeX">$40 ~\mu \text{s}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$10 ~\mu \text{s}$ </tex-math></inline-formula>, respectively. The output voltage is between 0.15 V (zero pressure) and 1 V (2 kPa) without an external amplifier. We demonstrate the pressure mapping over <inline-formula> <tex-math notation="LaTeX">$32\times32$ </tex-math></inline-formula> active-matrix pressure sensor array.
USING FRAMES OF SUBSPACES IN GALERKIN AND RICHARDSON METHODS FOR SOLVING OPERATOR EQUATIONS

In this paper, two iterative methods are constructed to solve the operator equation Lu = f where L : H → H is a bounded, invertible and selfadjoint linear operator on a separable Hilbert space H. By using the concept of frames of subspaces, which is a generalization of frame theory, we design some algorithms based on Galerkin and Richardson methods, and then we investigate the convergence and optimality of them. AMS Classification: 65F05, 46L05, 11Y50.
Topological derivative improved partial differential equation for infrared spectral data denoising

To reduce the influence of noise in infrared spectral signal measurement, a topological derivative improved partial differential equation method for infrared spectral data denoising is proposed. As an indicator function, topological derivative through a minimization process to find the best position to introduce disturbance, where are spectral edge points, then select the most excellent diffusion coefficient, so the cost of the minimum functional value. Based on the idea of topological optimization, it makes the lowest topological derivative to be optimum one. Then the diffusion is applied by using partial differential equation. Several simulated infrared spectral sequences are utilized to verify the performance of the proposed method. The experiment results show that our method is better in denoising.
Investigation of the Policy Effect of High-Speed Metropolitan Rail Service in Seoul Through Latent Class Modeling Analysis of Stated Preference Survey

The sprawl of megacities is increasing the need to improve public transit services to cover longer distances in shorter times than current services. High-speed metropolitan rail services have been introduced to satisfy the needs of passengers and are expected to alleviate the transportation problems caused by urban sprawl. However, the effectiveness of public transit demand inducement policies, which have been employed in various ways in South Korea, has been questioned. Thus, agencies responsible for high-speed metropolitan rail services should also evaluate whether such policies will work properly. The achievement of the policy can be evaluated as sufficiently inducing the demand of the target group, and investigated through the residence information and the current travel behavior. This study investigates the current travel behavior of users to be replaced when a new high-speed metropolitan rail service is introduced and directly analyzes the travel mode shifting effect. While previous studies focused on increasing the applicability to general services by classifying groups based on personal attributes, this study focuses on evaluating detailed policy achievements for specific services. We apply a latent class modeling approach using stated preference survey data for group classification. In particular, by employing the user’s current travel behavior as a class membership attribute, the characteristics of potential passengers of the high-speed metropolitan rail service are analyzed. The estimation results suggest that current travel behavior significantly classifies high-speed rail passengers. In addition, the policy achievement was investigated in detail by region and operation time, and several additional policy directions are presented to satisfy the policy goals.
Approaches to Outdoor Thermal Comfort Thresholds through Public Space Design: A Review

Based on the Koppen Geiger (KG) classification system, this review article examines existing studies and projects that have endeavoured to address local outdoor thermal comfort thresholds through Public Space Design (PSD). The review is divided into two sequential stages, whereby (1) overall existing approaches to pedestrian thermal comfort thresholds are reviewed within both quantitative and qualitative spectrums; and (2) the different techniques and measures are reviewed and framed into four Measure Review Frameworks (MRFs), in which each type of PSD measure is presented alongside its respective local scale urban specificities/conditions and their resulting thermal attenuation outcomes. The result of this review article is the assessment of how current practices of PSD within three specific subcategories of the KG ‘Temperate’ group have addressed microclimatic aggravations such as elevated urban temperatures and Urban Heat Island (UHI) effects. Based upon a bottom-up approach, the interdisciplinary practice of PSD is hence approached as a means to address existing and future thermal risk factors within the urban public realm in an era of potential climate change.