Miracle-dz/UniFAR-FTUs huggingface dataset:
Unit root bootstrap tests for AR(1) models

SUMMARY We propose bootstrap tests for unit roots in first-order autoregressive models and we establish their asymptotic validity both for independent and for autoregressive errors; in this case, the bootstrap methodology directly approaches the asymptotic distribution, making unnecessary the usual corrections due to dependence of innovations. We also present a Monte Carlo power study comparing these tests with existing alternative methods. For small samples, the power of the bootstrap test outperforms that of previous proposals.
Use of Action Label in Deep Predictive Learning for Robot Manipulation

Various forms of human knowledge can be explicitly used to enhance deep robot learning from demonstrations. Annotation of subtasks from task segmentation is one type of human symbolism and knowledge. Annotated subtasks can be referred to as action labels, which are more primitive symbols that can be building blocks for more complex human reasoning, like language instructions. However, action labels are not widely used to boost learning processes because of problems that include (1) real-time annotation for online manipulation, (2) temporal inconsistency by annotators, (3) difference in data characteristics of motor commands and action labels, and (4) annotation cost. To address these problems, we propose the Gated Action Motor Predictive Learning (GAMPL) framework to leverage action labels for improved performance. GAMPL has two modules to obtain soft action labels compatible with motor commands and to generate motion. In this study, GAMPL is evaluated for towel-folding manipulation tasks in a real environment with a six degrees-of-freedom (6 DoF) robot and shows improved generalizability with action labels.
Risk of waning humoral responses after inactivated or subunit recombinant SARS‐CoV‐2 vaccination in patients with chronic diseases: Findings from a prospective observational study in China

Heterogeneity of antibody responses has been reported in SARS‐CoV‐2 vaccination recipients with underlying diseases. We investigated the impact of the presence of comorbidities on the humoral response to SARS‐CoV‐2 vaccination in patients with chronic disease (PWCD) and assessed the effect of the number of comorbidities on the humoral response to vaccination. In this study, neutralizing antibodies (NAbs) and IgG antibodies against the receptor‐binding domain (RBD‐IgG) were monitored following a full‐course vaccination. In total, 1400 PWCD (82.7%, inactivated vaccines; 17.3%, subunit recombinant vaccine) and 245 healthy controls (65.7% inactivated vaccines, 34.3% subunit recombinant vaccine) vaccinated with inactivated or subunit recombinant SARS‐CoV‐2 vaccines, were included. The seroconversion and antibody levels of the NAbs and RBD‐IgG were different in the PWCD group compared with those in the control group. Chronic hepatitis B (odds ratio [OR]: 0.65; 95% confidence interval [CI]: 0.46–0.93), cancer (OR: 0.65; 95% CI: 0.42–0.99), and diabetes (OR: 0.50; 95% CI: 0.28–0.89) were associated with lower seroconversion of NAbs. Chronic kidney disease (OR: 0.29; 95% CI: 0.11–0.76), cancer (OR: 0.38; 95% CI: 0.23–0.62), and diabetes (OR: 0.37; 95% CI: 0.20–0.69) were associated with lower seroconversion of RBD‐IgG. Only the presence of autoimmune disease showed significantly lower NAbs and RBD‐IgG titers. Patients with most types of chronic diseases showed similar responses to the controls, but humoral responses were still significantly associated with the presence of ≥2 coexisting diseases. Our study suggested that humoral responses following SARS‐CoV‐2 vaccination are impaired in patients with certain chronic diseases.
High rayleigh number convection at infinite prandtl number with weakly temperature-dependent viscosity

Abstract The effects of high Rayleigh number convection for temperature-dependent viscosity at infinite Prandtl number are studied with three-dimensional direct numerical simulations (using a fully spectral method) in a wide box with dimensions 5 × 5 × 1. The form of the temperature-dependent viscosity decreases exponentially with the temperature. Solutions for an volumetrically averaged Rayleigh numbers up to 6.25 × 106 have been obtained for a viscosity contrast of 25. Both models with and without viscous dissipation and adiabatic heatings have been considered. There is a distinct difference in the plume dynamics between models with a dissipation number D = 0 and D = 0.3. At zero dissipation number the hot plumes extend up to the top, while plumes at D = 0.3 are cooled due to adiabatic expansion and do not extend throughout the entire layer. The cold descending flows occur in sheets and they form longer wavelength networks and can reach the bottom, regardless of the value of D. A time-varying depth-depe.
Visual Confined-Space Navigation Using an Efficient Learned Bilinear Optic Flow Approximation for Insect-scale Robots

Visual navigation for insect-scale robots is very challenging because in such a small scale, the size, weight, and power (SWaP) constraints do not appear to permit visual navigation techniques such as SLAM (Simultaneous Localization and Mapping) because they are likely to be too power-hungry. We propose to use a biology-inspired approach, which we term the bilinear optic flow approximation, that is more computationally efficient. We build on previous work that has shown that the bilinear approximation can be used for visual servoing. Here, we show that a bilinear approximator can be learned that is able to stabilize the heading of a robot while performing continuous forward motion in a corridor-shaped environment. This is a necessary capability for confined-space navigation that insect-sized robots are likely to perform. In this work, we describe the underlining methodology of the method and built a 2D visual simulation environment and omnidirectional camera model to validate our results.
Operational Energy Optimizing in Office Buildings: A Simulation-based Green Design Approach

The building sector consumes a sizable amount of global energy. Globally, developers are interested in reducing the cost of the operational energy of buildings. Green building certification has been initiated to promote the optimization of operational energy use and sustainable development. The Leadership in Energy and Environmental Design (LEED) certification guidelines provide a rating system for buildings to obtain green certification. This manuscript presents a case study that was carried out to estimate the potential operational energy savings in an office building construction project carried out in a tropical climate. A baseline design for the conventional building was carried out, based on the guidelines given in ASHRAE 90.1. To improve the energy savings, a green design was carried out, by following LEED guidelines, focusing on obtaining the LEED-Gold status. The consumption of energy by each equipment was calculated using Integrated Environmental Solution (IES) simulation software for a period of 365 days for the baseline and the proposed green designs. According to the findings, 23% of the electricity energy can be saved from the baseline design.
Cross-City Multi-Granular Adaptive Transfer Learning for Traffic Flow Prediction

Accurate traffic prediction is one of the most important techniques in building a smart city. Many works, especially deep learning models, have made great progress in traffic prediction based on rich historical data. However, many cities still suffer from the problem of data scarcity in many aspects. Some works use transfer learning to solve this kind of problem, but what and how to transfer is still an important problem. In this article, we propose a novel Cross-city Multi-Granular Adaptive Transfer Learning method named MGAT for traffic prediction with only a few data in the target city. We first use the meta-learning algorithm to train the model on multiple source cities to get a good initialization. And at the same time, the multi-granular regional characteristics of each source city will be obtained based on our model structure. Then we design an Adaptive Transfer module mainly composed of Spatial-Attention and Multi-head Attention mechanism to automatically select the most appropriate features from the multi-granular features trained from multiple source cities, to achieve the best transfer effect. We conduct extensive experiments on two kinds of real-world traffic datasets cross several cities. Experimental results with other state-of-the-art models demonstrate the effectiveness of the proposed model.
Current Status of Antibiotic Stewardship and the Role of Biomarkers in Antibiotic Stewardship Programs

The importance of antibiotic stewardship is increasingly emphasized in accordance with the increasing incidences of multidrug-resistant organisms and accompanying increases in disease burden. This review describes the obstacles in operating an antibiotic stewardship program (ASP), and whether the use of biomarkers within currently available resources can help. Surveys conducted around the world have shown that major obstacles to ASPs are shortages of time and personnel, lack of appropriate compensation for ASP operation, and lack of guidelines or appropriate manuals. Sufficient investment, such as the provision of full-time equivalent ASP practitioners, and adoption of computerized clinical decision systems are useful measures to improve ASP within an institution. However, these methods are not easy in terms of both time commitments and cost. Some biomarkers, such as C-reactive protein, procalcitonin, and presepsin are promising tools in ASP due to their utility in diagnosis and forecasting the prognosis of sepsis. Recent studies have demonstrated the usefulness of algorithmic approaches based on procalcitonin level to determine the initiation or discontinuation of antibiotics, which would be helpful in decreasing antibiotics use, resulting in more appropriate antibiotics use.
Ontogenetic changes in root and shoot respiration, fresh mass and surface area of Fagus crenata

Abstract Background and Aims To date, studies on terrestrial plant ecology and evolution have focused primarily on the trade-off patterns in the allocation of metabolic production to roots and shoots in individual plants and the scaling of whole-plant respiration. However, few empirical studies have investigated the root : shoot ratio by considering scaling whole-plant respiration at various sizes throughout ontogeny. Methods Here, using a whole-plant chamber system, we measured the respiration rates, fresh mass and surface area of entire roots and shoots from 377 Fagus crenata individuals, from germinating seeds to mature trees, collected from five different Japanese provenances. Non-linear regression analysis was performed for scaling of root and shoot respiration, fresh mass and surface area with body size. Key Results Whole-plant respiration increased rapidly in germinating seeds. In the seedling to mature tree size range, the scaling of whole-plant respiration to whole-plant fresh mass was expressed as a linear trend on the log–log coordinates (exponent slightly greater than 0.75). In the same body size range, root and shoot respiration vs. whole-plant fresh mass were modelled by upward-convex (exponent decreased from 2.35 to 0.638) and downward-convex trends (exponent increased from –0.918 to 0.864), respectively. The root fraction in whole-plant respiration, fresh mass and surface area shifted continuously throughout ontogeny, increasing in smaller seedlings during early growth stages and decreasing in larger trees. Conclusions Our results suggest a gradual shift in allocation priorities of metabolic energy from roots in seedlings to shoots in mature trees, providing insights into how roots contribute to shoot and whole-plant growth during ontogeny. The models of root : shoot ratio in relation to whole-plant physiology could be applied in tree growth modelling, and in linking the different levels of ecological phenomena, from individuals to ecosystems.
Improved excitation rate coefficients for the n = 2 and n = 3 levels of Ca XIX and Fe XXV including fine structure

Reently calculated collision strengths, including relativistic and resonance effects, are employed to compute Maxwellian averaged collision strengths for 78 transitions involving states of principal quantum numbers 2-1 and 3-1 in Ca XIX and Fe XXV. These rate parameters are tabulated at temperatures of interest in astrophysical and labortory plasmas with radiation in the hard X-ray wavelength range. For some transitions, significant differences are found with the earlier calculations of Pradhan, Norcross, and Hummer (1981). 10 references.
Factors Affecting the Success of Women Entrepreneurs in Egypt

Women's entrepreneurship is still a topic of interest on a global scale. According to studies by many scholars, the rate of female entrepreneurship activities and initiatives is considerably lower than those of men, especially in countries experiencing high gender inequality. The predominance of cultural practices exacerbating favoritism towards men is a major contributor to gender inequality in developing countries. Women become entrepreneurs for two reasons: out of choice or need. Despite the fact that women's participation in the workforce today reflects clear improvement, some studies found that women still have difficulty advancing their careers and, in particular, finding role models for effective managerial leadership. The purpose of this study is to explore factors affecting Egyptian women entrepreneurs’ success. This work is exploratory, as it follows a qualitative approach. The authors conducted eleven in-depth interviews with Egyptian women entrepreneurs from different sectors. The suggested conceptual framework presents several factors that affect the success of women entrepreneurs in Egypt, with different levels: personal factors (entrepreneurial mindset: opportunity recognition and attributes of leadership: motivation and passion, team builder), social support factors (friends & family support and family background and attitudinal drivers) and environmental factors (the use of social media and technology, the integration of sustainable environmental aspects into business strategy and the Egyptian entrepreneurial ecosystem). This study serves as a foundation for further research, analysis, and discussion of the interwind subjects of women, entrepreneurship, and leadership.
Analysis of the near-field ultrasonic scattering at a surface crack

The near-field scattering of a Rayleigh wave at a surface crack is analyzed with analytical and numerical calculations complemented by detailed experimental observations. These investigations are directed towards the development of inversion schemes for surface crack sizing in mechanical components. The near-field analysis is based on a procedure that allows filtering the Rayleigh wave from the other wave modes scattered at the defect. Pointwise measurements of the out-of-plane displacement using a laser interferometer lead to a complete displacement field image in the crack near field with high spatial resolution. The numerical calculations are compared with the analytical solution and the experimental data in order to validate specific crack modeling approaches and to identify parameters for surface crack characterization. The evaluation is carried out with respect to the stress fields at the crack tip, the surface displacement near field, Rayleigh wave transmission and reflection coefficients, and the time delay of Rayleigh wave transmission. The latter appears as the most suitable parameter for crack characterization due to the relative insensitivity of the measured values on the variability of the experimental conditions. The results of the present work also highlight differences between the scatterings at cracks and narrow slots (“artificial cracks”).
Bioclimatic interference in fertility in cows in the Amazon biome

The objective was to evaluate the correlation between environmental temperature-humidity index (THI), rectal temperature (RT), plasma cortisol concentration and pregnancy rate in embryo recipient cows in the Amazon biome. Embryo recipients (n=235) underwent estrus synchronization via simplification of the P36 protocol for Fixed-Time Embryo Transfer (TETF). On days zero (D0), eight (D8) and day 16 (D16), the rectal temperature of the recipient cows was measured, as well as the ambient temperature and relative humidity. On the 16th day after the start of the synchronization protocol (D16), each recipient received an embryo transferred after being diagnosed with a corpus luteum (CL) in one of the ovaries by ultrasonography (US) and, from each of them, a blood sample was collected by venipuncture of the coccygeal vein, in tubes with ethylenediaminetetraacetic acid (EDTA) as an anticoagulant to obtain blood plasma, where cortisol was measured by radioimmunoassay (RIA) in solid phase, using commercial kits. It was found that in the group of pregnant cows, the mean values of the parameters RT, plasma cortisol and THI (P < 0.05) were lower than those presented in the group of non-pregnant cows. Moreover, between the two groups there were positive and significant correlations between RT and THI (P < 0.05), as well as in relation to plasma cortisol parameters and THI (P < 0.05). It is concluded that it is possible to validate the use of RT and THI as an auxiliary tool for estimating plasma cortisol concentrations.
On a Generalized Fatou-Julia Theorem

In this article, we continue to explore some specific results in bicomplex dynamics. In particular, we give a bicomplex version of the so-called Fatou-Julia theorem. In fact, we give a complete topological characterization in ℝ4 of the bicomplex filled-Julia set for a quadratic polynomial in bicomplex numbers of the form w2 + c.
North‐south components of the annual asymmetry in the ionosphere

A retrospective study of the asymmetry in the ionosphere during the solstices is made using the different geospace parameters in the North and South magnetic hemispheres. Data of total electron content (TEC) and global electron content (GEC) produced from global ionospheric maps, GIM‐TEC for 1999–2013, the ionospheric electron content (IEC) measured by TOPEX‐Jason 1 and 2 satellites for 2001–2012, the F2 layer critical frequency and peak height measured on board ISIS 1, ISIS 2, and IK19 satellites during 1969–1982, and the earthquakes M5+ occurrences for 1999–2013 are analyzed. Annual asymmetry is observed with GEC and IEC for the years of observation with asymmetry index, AI, showing January > July excess from 0.02 to 0.25. The coincident pattern of January‐to‐July asymmetry ratio of TEC and IEC colocated along the magnetic longitude sector of 270° ± 5°E in the Pacific Ocean is obtained varying with local time and magnetic latitude. The sea/land differences in the F2 layer peak electron density, NmF2, and the peak height, hmF2, gathered with topside sounding data exhibit tilted ionosphere along the seashores with denser electron population at greater peak heights over the sea. The topside peak electron density NmF2, TEC, IEC, and the hemisphere part of GEC are dominant in the South hemisphere which resembles the pattern for seismic activity with dominant earthquake occurrence in the South magnetic hemisphere. Though the study is made for the hemispheric and annual asymmetry during solstices in the ionosphere, the conclusions seem valid for other aspects of seismic‐ionospheric associations with tectonic plate boundaries representing zones of enhanced risk for space weather.
Residual M-net with Frequency-Domain Loss Function for Latent Fingerprint Enhancement

Fingerprints generally deposited involuntarily on a surface and that usually require special chemical procedures to become visible are called latent fingerprints. These fingerprints have a relevant role in identifying individuals in forensic applications. In many cases, latent fingerprint images are inherently noisy, exhibit perturbations produced by their forming mechanism, and convey limited information, which requires enhancement procedures to improve the identification result. However, most existing methods successfully used to enhance fingerprints collected in controlled environments do not perform as well on latent fingerprints. In this research, we propose a latent fingerprint enhancement method based on a deep learning model that consists of a residual encoder-decoder architecture that optimizes a frequency-domain loss function during training. In addition, a procedure for synthetically generating a large set of labeled training data has been developed. Experiments with the MOLF database have shown that our proposed method improved the quality of fingerprints and resulted in better minutiae extraction, thus improving fingerprint identification performance. Compared with other methods published in the literature, the proposed method achieved better accuracies in ranks 1 to 30 according to CMC curves.
Strengthening Integrity and Fraud Awareness in Preventing Fraud During the Covid-19 Pandemic

The Covid-19 pandemic has impacted almost all socio-economic and business aspects. Changes in interaction patterns and a decrease in income lead to a higher potential for fraud risk. Management needs to take effective ways to mitigate fraud, especially fraud prevention as the most efficient strategy. This paper aims to explore and manage new challenges in terms of fraud risk related to the Fraud Triangle in non-digital financing companies. Using a quantitative approach, this study examines the effect of integrity and fraud awareness on fraud prevention according to the perception of the fraud detection team. 67 samples were collected and processed through PLS regression. The results show that R2 value is 0.592; integrity t-score is 3.315, p-value is 0.001; Fraud Awareness t-score is 2.119, p-value is 0.0341. Thus, integrity and fraud awareness have a positive and significant effect on fraud prevention in non-digital financing companies. However, there are some limitations that need to be investigated further, such as measurements for other fraud prevention strategies, other financial institutions, and other business industries that have been negatively affected by the Covid-19 pandemic.
In Vivo Antimalarial Activity of Trichosanthes cucumerina Against Plasmodium berghei NK65 in Mice

Undoubtedly, malaria is a vector-borne infectious disease that is increasingly being given attention by many researchers in their efforts to find the best drugs for its treatment. Four groups of mice (6-8 weeks old, 20-25 gram body weight (g bw) were inoculated with Plasmodium berghei NK65 intraperitoneally (i.p.) at 1.0 × 106 infected red blood cells (RBC) before being orally treated for the prophylactic and curative treatment regime with 0.2 mL of 100 mg/kg bw freeze-dried T. cucumerina aqueous extract. Parasitemia levels and inhibition rates were microscopically measured using Giemsa stained blood smear method. Trichosanthes cucumerina possessed strong antimalarial activities against P. berghei NK65 infection in mice. A significant correlation was successfully recorded between the survival time of the seven-day prophylactic treatment group (P7) with its ability to inhibit parasite growth as compared to the curative treatment groups. However, these values ​​are still incomparable to the control group treated with the commercial drugs primaquine and chloroquine. In addition, blood biochemical toxicity analysis of ALT, AST, ALP, and STP showed that acute and sub-acute toxicity treatments of T. cucumerina did not cause liver injury and were non-toxic to the animals. Thus, this study significantly proves (p≤0.05, n=6) that T. cucumerina has antiparasitic properties that can be manipulated as an alternative antimalarial drug.