Miracle-dz/UniFAR-FTUs huggingface dataset:
Un système dynamique d'ordre réduit basé sur une approche APR-POD pour l'étude de l'interaction écoulement turbulent-particules

Motive par l'etude numerique de la dispersion de particules dans un ecoulement turbulent, ce travail presente l'application et le developpement de methodes de reduction de modeles couplees a un systeme dynamique d'ordre bas pour les equations de Navier-Stokes. Ainsi, la premiere methode appliquee est la decomposition orthogonale aux valeurs propres (POD). Couplee a un systeme dynamique d'ordre faible obtenu par projection de Galerkin des equations de Navier-Stokes sur la base POD, cette methode montre son efficacite en terme de temps de simulation pour le calcul de la dispersion de particules. Cependant, la POD necessite au prealable un echantillonage temporel de l'ecoulement, ce qui est handicapant. Afin de palier ce probleme, l'alternative envisagee dans ce travail est l'utilisation d'une methode de reduction \emph{a priori}, l'APR, basee sur la construction iterative d'une base de l'ecoulement. La methode APR est d'abord testee dans des cas modeles simples : l'equation de convection-diffusion 2D et les equations de Burgers 1D et 2D. Comparee aux methodes de resolution classique, l'APR permet de diminuer fortement les temps de calcul tout en conservant une precision du meme ordre de grandeur. Les equations de Navier-Stokes sont ensuite resolues a l'aide d'un code volumes finis 2D, utilisant un decouplage vitesse-pression de type Van Kahn. Un algorithme de reduction a priori adapte a l'algorithme de projection est alors presente et applique pour le cas de la cavite entrainee 2D a Re=10000. Les resultats obtenus sur un court intervalle de temps sont assez encourageants. Enfin, une demarche d'avancement temporel basee sur le couplage d'APR et de systemes dynamiques est presentee.
A Retrospective Study to Examine Nutrition Based Risk and Protective Factors in Relation to Diarrhoea Incidence in Children Aged Less Than Two Years in Tanzania

Background: Diarrhea disorders account for a significant portion of the morbidity and mortality burden among children in resource-constrained settings, and they are economically significant to both families and health systems. In real sense, any intervention that has shown the potential to reduce diarrhea-related mortality and morbidity is valuable in terms of the global child health agenda. Objective: To explore the role of nutrition based risk and protective factors on diarrhea morbidity among children aged less than two years in Tanzania. Methods: We analyzed household-based data on risks and preventive interventions including exclusive breastfeeding, complementary feeding, water, sanitation hygiene, and vitamin A supplementation. Data from the Tanzania Demographic Health Survey (TDHS) of 2015/2016 were used to describe odds of diarrhoea morbidity in children aged 0-5 months and 6-23 months. Multivariate logic regression models were developed to identify risk factors. Results: Children aged less than 5 months, who were exclusively breastfed experienced a reduction in the odds of having diarrhoea by 72% (P-value <0.001), compared to those who were not exclusively breastfed. Children aged between 6 months and less than 23 months, from families with detergent at hand washing facility, experienced a reduction in the odds of having diarrhoea by 37% (P-value <0.01), compared to their peers in the other group. Diarrhoea odds were predicted to be higher in higher wealth quintile as compared to lowest group by 1.39 (P-value =0.028), 1.53 (P-value <0.01), 1.74 (P-value <0.01) and 1.78 (P-value =0.01) for second, middle, fourth to highest groups respectively. Conclusions: The data has demonstrated the important role of exclusive breastfeeding and sanitation on diarrhoea occurrence amongst children aged less than 23 months in Tanzania. Yet there are areas for which it remains inconclusive and requires further work to improve insights and strength of available evidence so far.
A DEMATEL approach for analyzing the influence factors of environment of verifying online disinformation

Disinformation has brought serious harm to the information ecology. The key point is how to mitigate it using disinformation verification. In this regard, this paper systematically analyze the importance and structural relationship among the influence factors of the online disinformation verification environment. It helps to deepen the understanding of online disinformation verification environment and better promote the realization of online disinformation verification. Based on the literature and interviews, 13 influence factors of online disinformation verification environment are identified by Delphi method. Using the matrix scoring questionnaires of experts and related personnel as samples, the Decisionmaking trial and evaluation laboratory method was used to analyze the relevant associations between the attributes. The results show that the level of network economic development, information literacy level, institutional implementation environment, education level, information analysis technology, information dissemination technology, and information collection technology are the key factors influencing the online disinformation verification environment.
The effect of climate change on Arcto‐Tertiary Mexican beech forests: Exploring their past, present, and future distribution

Abstract Fagus mexicana Martínez (Mexican beech) is an endangered Arcto‐Tertiary Geoflora tree species that inhabit isolated and fragmented tropical montane cloud forests in eastern Mexico. Exploring past, present, and future climate change effects on the distribution of Mexican beech involves the study of spatial ecology and temporal patterns to develop conservation plans. These are key to understanding the niche conservatism of other forest communities with similar environmental requirements. For this study, we used species distribution models by combining occurrence records, to assess the distribution patterns and changes of the past (Last Glacial Maximum), present (1981–2010), and future (2040–2070) periods under two climate scenarios (SSP 3‐7.0 & SSP 5‐8.5). Next, we determined the habitat suitability and priority conservation areas of Mexican beech as associated with topography, land cover use, distance to the nearest town, and environmental variables. By considering the distribution of Mexican beech during different periods and under different climate scenarios, our study estimated that high‐impact areas of Mexican beech forests were restricted to specific areas of the Sierra Madre Oriental that constitute refugia from the Last Glacial Maximum. Regrettably, our results exhibited that Mexican beech distribution has decreased 71.3% since the Last Glacial Maximum and this trend will for the next 50 years, migrating to specific refugia at higher altitudes. This suggests that the states of Hidalgo, Veracruz, and Puebla will preserve the habitat suitability features as ecological refugia, related to high moisture and north‐facing slopes. For isolated and difficult‐to‐access areas, the proposed methods are powerful tools for relict‐tree species, which deserve further conservation.
Recognition of common fish images by deep convolutional neural networks

A fast and accurate fish identification system is urgently needed for the development of fishery industry. In this paper, ten kinds of common fish are taken as the research object, and the existing achievements of deep Convolutional Neural Networks in the field of image classification are used to provide technical support for the establishment of intelligent and efficient fish recognition system in fishery production. The research mainly includes three parts : data collection, model building and optimization comparison. Firstly, fish images are collected through web crawler and field collection, and then the collected image format is normalized to establish a fish data set. data augmentation is used to expand the training dataset and reduce the dependence of the model on the original dataset. Secondly, AlexNet, VGGNet and ResNet convolutional neural networks are used for image classification tools, and the generalization ability of the model is improved by combining the transfer learning method. Finally, through the comparison of the training results of each model, the ResNet-50 network model with better performance based on transfer learning is found as the main model of fish recognition, and its recognition rate is 98.06 %.
Sine dot product

The Sine Dot Product is an original study introduced by the author into the mathematical domain. The main goal of introducing this new study is to find applications and to facilitate many complicated issues that are difficult to resolve using the traditional Vectorial product (Cross Product) and the Dot product. The idea of the Sine Dot Product is to multiply two vectors and the result will be a Scalar equal to the magnitude of the two vectors multiplied by sine instead of cosine. In this paper, a brief study is introduced with the definition of the Sine Dot Product and simple applications are developed as the Magnitude of the Sine Dot Product will give the Area of the two vectors, moreover one can find the equation of a plane in 3-Dimensions using the Sine DotProduct. The method of using the Sine Dot Product instead of the Cross Product and Dot Product is much easier to find the equation of a plane in 3-Dimensions. Many studies will follow this one in order to find more important applications of this new Product between vectors.
Compact Self-Dual Manifolds with Torus Actions

We show that a compact self-dual four-manifold with a smooth action of a two-torus and with non-zero Euler characterestic is necessarily diffeomorphic to a connected sum of copies of complex projective planes, and furthermore the self-dual structure is isomorphic to one of those constructed by Joyce in [11]. This settles a conjecture of Joyce [11] affirmatively. Our method of proof is to show, by complex geometric techniques, that the associated twistor space, which is a compact complex threefold with the induced holomorphic action of algebraic two-torus, has a very special structure and is indeed determined by a certain invariant which is eventually identified with the invariant associated with the Joyce’s construction of his self-dual manifolds.
Multiparameter Processes: An Introduction to Random Fields

Discrete-Parameter Random Fields: Discrete Parameter. Martingales. Two Applications in Analysis. Random Walks. Multiparameter Walks. Gaussian Random Walks. Limit Theorems. - Continuous-Parameter Random Fields: Continuous Parameter Martingales. Constructing Markov Processes. Generation of Markov Processes. Probabilistic Potential Theory. Multiparameter Markov Processes. Brownian Sheet and Potential Theory. - Appendices: Kolmogorov's Consistency Theorem. Laplace Transforms. Hausdorff Dimensions and Measures. Energy and Capacity.
Roles of some functional hormones among pregnant women infected with toxoplasmosis

Toxoplasmosis represents one of the most widespread zoonosis caused by T. gondii parasite, an intracellular protozoan with a worldwide distribution. This disease infects all warm-blooded animals, including humans. The current study aimed to detect the role of some functional hormones among pregnant women suffering from Toxoplasma gondii. The study was carried out during the period from October 2021 to first February 2022 on (200) pregnant women who attended to various governmental hospitals in Maysan province of Iraq with their ages ranged from (19-35) years. Venous blood samples were collected from all pregnant women enrolled in this study. The results showed that of the total (200) pregnant women, 97(48.50%) had positive IgG antibodies to toxoplasmosis, while 103(51.50%) had negative IgG antibodies to toxoplasmosis. The results also exhibited that of the total (200) pregnant women, 11(5.50%) had positive IgM antibodies to toxoplasmosis, while 189(94.50%) had negative IgM antibodies to toxoplasmosis. In patients with IgG positive antibodies, the mean luteinizing hormone (LH) level was (2.69 ±0.33), and in patients with IgG negative antibodies, the mean LH level was (2.23 ±0.24), while in patients with IgG positive antibodies, the mean follicular stimulating hormone (FSH) level was (5.48 ±1.35),,,,
Do buprenorphine doses and ratios matter in medication assisted treatment adherence

Introduction Buprenorphine (BUP), generally prescribed as buprenorphine/naloxone, is a key component of medication-assisted treatment (MAT) to manage opioid use disorder. Studies suggest higher doses of BUP increase treatment adherence. Routine urine drug screens (UDS) assist in monitoring MAT adherence via measurement of excreted BUP and its metabolite, norbuprenorphine (NBP). The clinical significance between BUP/NBP concentrations and their ratios for assessing adherence and substance use is not well-described. Methods We conducted a single-center, retrospective chart review of 195 clients age ≥18 years enrolled in a local MAT program from August 2017 to February 2021. Demographics, BUP doses, prescription history, and UDS results were collected. Participants were divided based on MAT adherence (<80% vs ≥80%) and median total daily dose (TDD) of BUP (≥16 mg vs <16 mg) in addition to pre- and post-COVID-19 cohorts. Results Median BUP/NBP urinary concentrations were significantly correlated with MAT adherence (P < .0001 for each) and a reduced percentage of positive UDS for opioids (P = .0004 and P < .0001, respectively) but not their ratios. Median TDD of BUP ≥16 mg (n = 126) vs <16 mg (n = 68) was not correlated with MAT adherence (P = .107) or incidence of nonprescription use (P = .117). A significantly higher incidence of UDS positive for opiates (P = .049) and alcohol (P = .035) was observed post-COVID-19. Discussion Clients appearing adherent to MAT who had higher concentrations of urinary BUP/NBP demonstrated a reduced incidence of opioid-positive UDS independent of the BUP dose prescribed. An increase in opioid- and alcohol-positive UDSs were observed during the COVID-19 pandemic.
Memperluas Agenda Studi Keamanan Nasional: Politik, Hukum dan Strategi

National security is the first and foremost responsibility of a nation. A nation isconsidered a strong nation once it is able to secure the livelihood of the people and thewellbeing of the nation itself. Yet the world is evolving quickly and new technologies andinnovations bring about new threats and opportunities towards national security. Thisarticle aims to describe the expansion of politics, laws, and strategies within the study ofnational security. Content analysis method will be used in this article. From more than20 articles referenced here, it can be summarized that changes in strategic environmentis heavily affected by the latest industrial revolution, the industry 4.0. Thus, this bringsabout new challenges such as cyber threats. The researcher then concluded that thesethreats could affect a nation strategically. These threats then focused on political threatsof collective security, current law threats which requires cyber law, and strategic threatswhich is cyber security.Keywords: National Security, Strategy, Politic, Law
A survey of Low Luminosity Compact sources and its implication for evolution of radio-loud AGNs. I. Radio data

We present a new sample of Compact Steep Spectrum (CSS) sources with radio luminosity below 10^26 W/Hz at 1.4 GHz called the low luminosity compact (LLC) objects. The sources have been selected from FIRST survey and observed with MERLIN at L-band and C-band. The main criterion used for selection was luminosity of the objects and approximately one third of the CSS sources from the new sample have a value of radio luminosity comparable to FRIs. About 80% of the sources have been resolved and about 30% of them have weak extended emission and disturbed structures when compared with the observations of higher luminosity CSS sources. We studied correlation between radio power and linear size, and redshift with a larger sample that included also published samples of compact objects and large scale FRIIs and FRIs. The low luminosity compact objects occupy the space in radio power versus linear size diagram below the main evolutionary path of radio objects. We suggest that many of them might be short-lived objects, and their radio emission may be disrupted several times before becoming FRIIs. We conclude that there exists a large population of short-lived low luminosity compact objects unexplored so far and part of them can be precursors of large scale FRIs.
Comparison of the Analgesic Effect of Subcutaneous Bupivacaine Infiltration and Intravenous Diclofenac vs. Intravenous Diclofenac Monotherapy After Inguinal Hernioplasty: A Retrospective Study

Background Postoperative pain is a significant problem encountered by patients after a surgical intervention, and there is a crucial need for effective postoperative pain control. The studies have shown that multimodal analgesia and wound infiltration are effective ways to reduce this pain and have a substantial role in the reduction of postoperative medications requirement. This study aimed to evaluate the effect of subcutaneous infiltration of bupivacaine hydrochloride and intravenous (IV) diclofenac as postoperative pain relief in adults undergoing inguinal hernia repair. Methods A single-center retrospective study included 104 patients aged 18-65 undergoing unilateral inguinal herniorrhaphy at the selected hospital. The patients were in two groups of 52 each. Group A received a 75 mg dose of IV diclofenac plus a subcutaneous injection of 10 mL of bupivacaine hydrochloride (HCl) 0.5% while Group B only received the IV diclofenac without the bupivacaine injection. The postoperative pain was assessed at one, two, three, six, and 12 hrs after the operation using the visual analog scale (VAS), which exhibited a range of pain from zero (no pain) to 10 (extreme pain). Results Of a total of 104 patients, 92% of patients were male. The patients' mean age was 36 ± 11 years, and the mean body mass index (BMI) was 22 ±3 kg/m2. American Society of Anesthesiologists physical class I was similar in both groups (90.4% versus 84.6%). Patients in Group A had significantly lower VAS pain scores at one, two, three, six, and 12 hrs after the operation and a longer emergence time than Group B (all p-values were < 0.001). Subcutaneous bupivacaine infiltration and IV diclofenac were also found to be an effective analgesic technique in open hernia repair with mesh (p-value < 0.001 for all). Conclusion Subcutaneous injection of bupivacaine combined with IV diclofenac provides superior analgesia to monotherapy intravenous diclofenac after inguinal hernia repair.
Resolution-Normalizing Image Stitching for Long-Linear-Array and Wide-Swath Whiskbroom Payloads

Affected by the large and inconsistent geometric distortion deriving from long-linear-array and wide-swath whiskbroom (LWW) imaging and the small overlap area of adjacent images, the conventional stitching methods based on feature matching greatly suffer from the severe misalignment, ghosting effect, and distortion in overlapping and nonoverlapping areas, respectively. Here, in view of these problems, this letter proposes a resolution-normalizing stitching method for LWW images. First, considering the variation of scan angle, earth curvature, and pixel position along track, we establish a resolution characterization model to calculate the accurate ground sampling distance (GSD) anywhere in the field of view (FOV). Then, accordingly, the resolution-normalizing method comprising GSD allocation and gray-value interpolation is proposed to reproject the original adjacent images for eliminating the resolution inconsistency along track. Finally, the normalized images were stitched based on the perspective transformation with matching corresponding pairs. Experimental results evaluated on the images of thermal infrared spectrometer (TIS) aboard Sustainable Development Goals Satellite-1 (SDGSAT-1) show that the stitching accuracy of the proposed method can be around 0.5 pixels, and more importantly, the ghosting effects and projection distortions are reduced effectively.
Detailed Multifrequency Study of a Rapid VHE Flare of Mrk501 in May 2009

We present observations of the gamma-ray blazar Markarian 501 between April 17 and May 5, 2009, with the Whipple 10-m telescope, VERITAS, the Fermi Large Area Telescope (LAT), Swift and RXTE as part of a 4.5-month multi-wavelength campaign. The presentation will focus on the strong very high energy (VHE) gamma-ray activity detected on May 1st with Whipple and VERITAS, when the measured flux (E > 400 GeV) reached five times the flux of the Crab Nebula, coincident with an increase in the optical polarization by a factor of 5, and a rotation of the polarization angle by 15 degrees. We also show that, during this 3-week period, the largest flux and spectral variability is seen at the highest energies of the broadband spectral energy distribution.
Periodic autoregressive time-frequency analysis for monitoring of rotating machinery with variable period

The development of a periodic autoregressive spectral estimator which is insensitive to variations in period is considered. The extended Kalman filter is investigated for estimation of the period. This estimate is then incorporated into a rotational framework to produce a time-varying spectral estimate for a nominally periodic system. It is expected that the method will be useful for monitoring the intracycle behaviour of rotating machinery such as diesel engines, compressors, gears and bearings. Use of the short time Fourier transform for variable speed envelope analysis is also shown to be a necessary tool for detection of faults in low, variable speed rotating machinery.
Towards domain-independent, task-oriented, conversational adequacy

Past approaches for solving MDPs have several weaknesses: 1) Decision-theoretic computation over the state space can yield optimal results but scales poorly. 2) Value-function approximation typically requires human-specified basis functions and has not been shown successful on nominal ("discrete") domains such as those in the ICAPS planning competitions. 3) Replanning by applying a classical planner to a determinized domain model can generate approximate policies for very large problems but has trouble handling probabilistic subtlety [Little and Thiebaux, 2007]. This paper presents RETRASE, a novel MDP solver, which combines decision theory, function approximation and classical planning in a new way. RETRASE uses classical planning to create basis functions for value-function approximation and applies expected-utility analysis to this compact space. Our algorithm is memory-efficient and fast (due to its compact, approximate representation), returns high-quality solutions (due to the decision-theoretic framework) and does not require additional knowledge from domain engineers (since we apply classical planning to automatically construct the basis functions). Experiments demonstrate that RETRASE outperforms winners from the past three probabilistic-planning competitions on many hard problems.