Miracle-dz/UniFAR-FTUs huggingface dataset:
Géochimie des black shales du Jurassique supérieur de la plate-forme russe. Processus de sédimentation et de préservation de la matière organique

La plate-forme russe a ete le siege d'un important depot de matiere organique (MO) au cours du Volgien moyen. La formation qui en resulte, montre des alternances decimetriques de niveaux marneux et de black shales. Nous avons etudie cette formation sur deux sites, Gorodische et Kashpir, situes dans la region moyenne de la Volga, afin de determiner les processus de sedimentation et de preservation de la matiere organique. Une premiere etude globale du sediment et de la matiere organique a ete menee sur un grand nombre d'echantillons provenant des deux sites. Les resultats indiquent que les echantillons de Gorodische et de Kashpir presentent des caracteristiques geochimiques globales proches (IH, COT, CaCO3.), ce qui atteste de conditions de depot et de preservation de la MO similaires sur l'ensemble du bassin de la moyenne Volga. La palynologie montre que les echantillons sont domines par la MO amorphe (MOA) et indique que les variations verticales d'IH et COT observees le long de la coupe de Gorodische ne sont pas liees a des variations dans la contribution relative de MO terrestre et de MO marine. Les echantillons de Gorodische ont pu etre repartis selon trois groupes presentant des caracteristiques morphologiques et geochimiques differentes : (i) MOA grise pour les kerogenes peu aliphatiques, pauvres en soufre organique et presents dans les echantillons de plus faible COT (ii) MOA orange heterogene pour les kerogenes relativement aliphatiques, moyennement enrichis en soufre, presents dans les echantillons de COT intermediaire et (iii) MOA orange pure pour les kerogenes tres aliphatiques et enrichis en soufre organique, presents dans les niveaux de plus fort COT. L'analyse geochimique detaillee (spectroscopie et pyrolyse) des trois kerogenes representatifs de ces trois groupes indique l'origine phytoplanctonique de la MO. Une faible contribution de materiel bacterien est egalement notee. Les differents processus de preservation de la MO ont egalement ete mis en evidence : la MOA orange pure s'est essentiellement formee par sulfuration naturelle de lipides et de sucres sous des conditions anoxiques ; la MOA grise s'est principalement formee par degradation-recondensation et, dans une moindre mesure, par preservation selective de parois d'algues sous des conditions principalement oxygenees ; la MOA orange heterogene intermediaire entre les deux autres types, est constituee de melanoidines et de materiel soufre, elle s'est formee sous des conditions variables globalement dysoxiques. Les trois kerogenes montrent egalement une importante contribution de lipides incopores par reticulation oxydative. La combinaison des deux approches, geochimie globale et detaillee, permet de proposer une reconstruction du paleoenvironnement et de son evolution au cours du depot de la formation.
SIW Based D-Band Single and 2 × 2 MIMO Elliptically Tapered Slot Antenna

In this paper, the substrate integrated waveguide (SIW) based single and <inline-formula> <tex-math notation="LaTeX">$2\times 2$ </tex-math></inline-formula> multiple input multiple output (MIMO) elliptically tapered slot antennas (ETSA) have been demonstrated at the D-band. The width of the coupling SIW line is selected to operate at the TE10-mode within the frequency range of interest. The elliptically tapered opening is designed in front of the upper and lower metal layers at the radiating end of the SIW line. The outer sides of elliptically tapered metal extensions are corrugated to improve the impedance matching. For measurement, three separate SIW based transitions working at different frequency ranges are integrated with single SIW ETSA and named as Ant-1, Ant-II, and Ant-III. A setup was constructed for far-field measurements within the laboratory where only the 2D radiation patterns and gains can be measured. The Ant-I, Ant-II, and Ant-III prototypes achieved a measured <inline-formula> <tex-math notation="LaTeX">$\vert \text{S}_{11}\vert < -10$ </tex-math></inline-formula> dB of 20 GHz (110–130 GHz), 28.6 GHz (130–158.6 GHz) and 16 GHz (154–170 GHz) with peak gains of 12.85, 12.86, and 10.4 dBi, respectively. For <inline-formula> <tex-math notation="LaTeX">$2\times 2$ </tex-math></inline-formula> MIMO versions, the S-parameters, and condition number for line-of-sight scenario were measured.
User Pairing for Delay-Limited NOMA-Based Satellite Networks with Deep Reinforcement Learning

In this paper, we investigate a user pairing problem in power domain non-orthogonal multiple access (NOMA) scheme-aided satellite networks. In the considered scenario, different satellite applications are assumed with various delay quality-of-service (QoS) requirements, and the concept of effective capacity is employed to characterize the effect of delay QoS limitations on achieved performance. Based on this, our objective was to select users to form a NOMA user pair and utilize resource efficiently. To this end, a power allocation coefficient was firstly obtained by ensuring that the achieved capacity of users with sensitive delay QoS requirements was not less than that achieved with an orthogonal multiple access (OMA) scheme. Then, considering that user selection in a delay-limited NOMA-based satellite network is intractable and non-convex, a deep reinforcement learning (DRL) algorithm was employed for dynamic user selection. Specifically, channel conditions and delay QoS requirements of users were carefully selected as state, and a DRL algorithm was used to search for the optimal user who could achieve the maximum performance with the power allocation factor, to pair with the delay QoS-sensitive user to form a NOMA user pair for each state. Simulation results are provided to demonstrate that the proposed DRL-based user selection scheme can output the optimal action in each time slot and, thus, provide superior performance than that achieved with a random selection strategy and OMA scheme.
The Development of a Learning Activity Model for Promoting Digital Technology and Digital Content Development Skills

The objective of this research was to develop an instructional model to enhance digital technology and digital content development skills. The model consisted of four components: lectures, hands-on exercises, group projects, and online learning resources. To identify the underlying components of the model, factor analysis was conducted. The factor analysis results showed that the four components explained a cumulative 90.2% of the variance in the learning model. The learning model was delivered over 16 weeks and covered topics such as digital technology basics, graphics and animation design, virtual learning technology, digital content marketing, collaboration and communication tools, social media and digital marketing, and ethics and privacy in the digital world. The model’s effectiveness was assessed using quantitative and qualitative methods, including t-tests and Pearson correlations. The results of the t-tests indicated a significant improvement in both digital technology skills and digital content development skills after participation in the learning model (p < 0.05). The Pearson correlations further showed a strong relationship between digital technology and digital content development skills (r = 0.78, p < 0.01).
Effects of carbohydrate drinks ingestion on executive function in athletes: a systematic review and meta-analysis

Background Carbohydrates are often used as boosters for endurance and high-intensity exercise. However, it is unclear whether carbohydrate drinks intake before or during exercise can affect specific domains of cognitive function, such as Executive Function (EF). Methods Following the guidance of PRISMA 2020, we searched six major databases including PubMed, WOS, SPORTDiscus, Cochrane, Embase, and Scopus. Outcomes were presented in the form of Reaction Time (RT), Accuracy (ACC), and Scores (Score) for performing EF tests. Effect sizes were calculated from the test results of EF and expressed as standardized mean differences (SMDs). After analyzing the overall results, we performed subgroup analyses based on the athletes’ program characteristics. Results After retrieving a total of 5,355 articles, ten randomized controlled trials (RCTs) were identified and included in this review. The overall results showed that the intake of carbohydrate drinks before or during exercise did not have a significant effect on the reduction of EF after exercise (ACC (−0.05 [−0.27, 0.18]); RT (−0.18 [−0.45, 0.09]); Score (0.24 [−0.20, 0.68])). The subgroup analyses based on open skill sports and close skill sports also showed invalid results, but the results of RT ended up with different preference (ACC of open skill sports athletes (−0.10 [−0.34, 0.14]); RT of open skill athletes (−0.27 [−0.60, 0.07]); RT of close skill athletes (0.29 [−0.24, 0.82])). Conclusion The intake of 6–12% of single or mixed carbohydrates before or during exercise was not significantly effective in reducing the decline in EF after exercise. Our findings may have been influenced by the type of intervention, dose, mode of administration, or individual variability of the included subjects.
Initial landscape changes associated with Marcellus shale developmentimplications for forests and wildlife

Marcellus shale development is occurring rapidly across Pennsylvania. We conducted a geographic information system (GIS) analysis using available Pennsylvania Department of Environmental Protection permit data, before and after photos, ground-truthing, and fi eld measurements to describe landscape change within the fi rst 3 years of active Marcellus exploration and development.
Employees’ metacognitive knowledge and skills assessment in tourism and hospitality

This research explores academic knowledge, cognitive, emotional, and soft skills, according to the employees’ perceptions, that lead to better service provision and career development enhancement in the tourism and hospitality industry. Moreover, the research explores the possible differences and correlations in reference to five individual traits: the educational background, the tourism and hospitality sectors, the seasonal or full-time character of the organization, the location of the organization, and the working experience derived. In order to investigate the perceptions of employees, 102 online questionnaires were fully completed. Cronbach’s Alpha index, descriptive statistical analysis, correlations between first-ordinal factors, and several MANOVA tests provide information regarding the metacognitive assessment of the above-mentioned domains. According to their responses, the most important academic knowledge that entails the international nature of the Tourism and Hospitality Industry, is ‘International Hospitality Management’. English is the most important foreign language, and Tourism Business Management is the most essential academic knowledge. The most important skills for the Tourism and Hospitality Industry that arise from the research are those of ‘problem solving’, ‘dealing with clients’, ‘customer service’, ‘crisis management’, ‘self-control, and ‘empathy’. The research concluded that, according to employees’ responses, skills and knowledge in the tourism and hospitality industry are generic and universal in their nature and applicability, and they do not differ regarding their individual characteristics. The analysis of the research data provides fruitful information regarding the most important and essential skills and knowledge for the tourism and hospitality industry.
Elucidating the Role of Plant Extracts Mediated Gold Nanoparticles as Smart Antimicrobials: Two-Way Attack

Pathogenic bacteria remain the primary health concern even after developing a broad spectrum of antibiotics. The emergence of drug-resistant strains increased mortality, perhaps resulting in a never-ending future pandemic. The researchers are currently concentrating their efforts on nanotechnology-based therapies to counteract resistance. The present review focuses on the antimicrobial characteristics of plant-mediated gold nanoparticles (Au NPs). First, the methodology and importance of green synthesis are highlighted. Variability in NPs characterization methods was identified, with dynamic light scattering, zeta potential, and thermogravimetric analysis limited to a few investigations. Second, the Au NPs synthesized using different plant extracts were found to be broad-spectrum antimicrobial agents against Pseudomonas aeruginosa, Escherichia coli, Cryptococcus neoformans, Candida glabrata, Aspergillus niger, etc. The lowest minimum inhibitory concentrations range (1.95–15.62 µg/mL) was observed with Au NPs synthesized using Thymus vulgaris extract against Staphylococcus aureus, P. aeruginosa, Bacillus subtilis, and E. coli. The effect was more pronounced with smaller NPs (<10 nm). The activity of Au NPs might be mediated through a two-way attack which includes nanoparticles’ diverse mechanisms like reactive oxygen species generation, etc., and surface-attached phytocompounds such as flavonoids, alkaloids, phenolics, terpenoids, tannins, etc. The futuristic role of nanotechnology-based interventions in managing microbial infections is imperative. Synergistic interactions of Au NPs with antibiotics, toxicity profiling, stability, and bioavailability could be major areas of NPs research.
Determinants of Inadequate Empiric Antimicrobial Therapy in ICU Sepsis Patients in Al-Madinah Al-Munawwarah, Saudi Arabia: A Comparison of Artificial Neural Network and Regression Analysis

In the management of sepsis, providing adequate empiric antimicrobial therapy is one of the most important pillars of sepsis management. Therefore, it is important to evaluate the adequacy of empiric antimicrobial therapy (EAMT) in sepsis patients admitted to intensive care units (ICU) and to identify the determinants of inadequate EAMT. The aim of this study was to evaluate the adequacy of empiric antimicrobial therapy in patients admitted to the ICU with sepsis or septic shock, and the determinants of inadequate EAMT. The data of patients admitted to the ICU units due to sepsis or septic shock in two tertiary healthcare facilities in Al-Madinah Al-Munawwarah were retrospectively reviewed. The current study used logistic regression analysis and artificial neural network (ANN) analysis to identify determinants of inadequate empiric antimicrobial therapy, and evaluated the performance of these two approaches in predicting the inadequacy of EAMT. The findings of this study showed that fifty-three per cent of patients received inadequate EAMT. Determinants for inadequate EAMT were APACHE II score, multidrug-resistance organism (MDRO) infections, surgical history (lower limb amputation), and comorbidity (coronary artery disease). ANN performed as well as or better than logistic regression in predicating inadequate EAMT, as the receiver operating characteristic area under the curve (ROC-AUC) of the ANN model was higher when compared with the logistic regression model (LRM): 0.895 vs. 0.854. In addition, the ANN model performed better than LRM in predicting inadequate EAMT in terms of classification accuracy. In addition, ANN analysis revealed that the most important determinants of EAMT adequacy were the APACHE II score and MDRO. In conclusion, more than half of the patients received inadequate EAMT. Determinants of inadequate EAMT were APACHE II score, MDRO infections, comorbidity, and surgical history. This provides valuable inputs to improve the prescription of empiric antimicrobials in Saudi Arabia going forward. In addition, our study demonstrated the potential utility of applying artificial neural network analysis in the prediction of outcomes in healthcare research.
An Instrumented Mouthguard for Real-Time Measurement of Head Kinematics under a Large Range of Sport Specific Accelerations

Background: Head impacts in sports can produce brain injuries. The accurate quantification of head kinematics through instrumented mouthguards (iMG) can help identify underlying brain motion during injurious impacts. The aim of the current study is to assess the validity of an iMG across a large range of linear and rotational accelerations to allow for on-field head impact monitoring. Methods: Drop tests of an instrumented helmeted anthropometric testing device (ATD) were performed across a range of impact magnitudes and locations, with iMG measures collected concurrently. ATD and iMG kinematics were also fed forward to high-fidelity brain models to predict maximal principal strain. Results: The impacts produced a wide range of head kinematics (16–171 g, 1330–10,164 rad/s2 and 11.3–41.5 rad/s) and durations (6–18 ms), representing impacts in rugby and boxing. Comparison of the peak values across ATD and iMG indicated high levels of agreement, with a total concordance correlation coefficient of 0.97 for peak impact kinematics and 0.97 for predicted brain strain. We also found good agreement between iMG and ATD measured time-series kinematic data, with the highest normalized root mean squared error for rotational velocity (5.47 ± 2.61%) and the lowest for rotational acceleration (1.24 ± 0.86%). Our results confirm that the iMG can reliably measure laboratory-based head kinematics under a large range of accelerations and is suitable for future on-field validity assessments.
Some reflections about an Alabaster stele from Mari (Syria) and its possible relations to the Western Mediterranean

Resumen El presente articulo trata de una estela de alabastro con decoracion antropomorfa descubierta en las excavaciones de (Syria). Ya que en el contexto del Bronce Antiguo del Proximo Oriente contamos con pocas piezas parecidas, subrayamos sus posibles paralelos en el Mediterraneo Occidental. Asi encontramos en la Peninsula Iberica todos los elementos presentes en la estela de Mari. Entre los artefactos tratados destacamos en primer lugar las placas de pizarra y la ceramica simbolica con su simbologia de ojos. Esto se engloba en la cuestion de las relaciones del Calcolitico de la Peninsula Iberica con Oriente. Palabras clave: Estela de alabastro - Mari- simbologia de ojos – placas de pizarra- Peninsula Iberica – Contactos a traves del Mediterraneo. Abstract The present articles treats an alabaster stele with anthropomorphic decoraction discovered in the excavations of Mari (Syria)1. As there are only a few comparable objects in its Near Eastern Early Bronze Age context, special attention is drawn to the possible parallels in the Western Mediterranean. In fact it is on the Iberian Peninsula were all elements and symbols united on the Mari stele occur. Among the artefact groups in question we mention especially the slate slab idols and the so called Symbolkeramik, all with oculus symbolism. This implies the question of the eastern relations of Iberian Chalcolithic during the third millennium. Keywords: Alabaster stele- Mari- Oculus symbolism- Slate slab idols- Symbolkeramik- Iberian Peninsula- Mediterranean connections
Accumulation of advanced glycation end products in the peritoneal vasculature of continuous ambulatory peritoneal dialysis patients with low ultra-filtration.

BACKGROUND Ultra-filtration failure is a serious complication of long-term continuous ambulatory peritoneal dialysis (CAPD). This complication is related to histological changes of the peritoneum, i.e. severe interstitial fibrosis and microvascular sclerosis. Although their pathogenesis has not been elucidated yet, advanced glycation end products (AGEs) have been shown to accumulate in the peritoneal tissue of CAPD patients. METHODS Peritoneal biopsy specimens from 14 CAPD patients with low ultra-filtration (n = 9) and high ultra-filtration (n = 5) capacity were immunohistochemically investigated using a monoclonal antibody against AGEs (6D12). The severity of peritoneal fibrosis, microvascular sclerosis and intensity of AGE accumulation were semi-quantitatively evaluated. Peritoneal ultra-filtration capacity was evaluated by calculating daily ultrafiltration volume per body weight (UFV/BW) and D/D0 (glucose) of the peritoneal equilibration test. RESULTS In all patients with low ultra-filtration, AGE accumulated in the peritoneal fibrous tissue and microvascular walls. Remarkably, AGE accumulated more intensely in hyalinized fibrosis of small venular media. Extent of AGE accumulation in peritoneal interstitium and vascular walls correlated with the progression of interstitial fibrosis (rho = 0.727, P = 0.0088) and vascular sclerosis (rho = 0.915, P = 0.001). UFV/BW was inversely correlated to interstitial fibrosis (rho = -0.660, P = 0.0174), microvascular sclerosis (rho = -0.671, P = 0.0155) and microvascular AGE accumulation (rho = -0.678, P = 0.0145). CONCLUSIONS In CAPD patients, AGE formation in the peritoneum correlates with the development of severe interstitial fibrosis and microvascular sclerosis, which is associated clinically with impaired peritoneal ultra-filtration.
Detection of abrupt changes in glacier mass balance in the Tien Shan Mountains

Abstract Based on glacier mass-balance records collected, compiled and published by the World Glacier Monitoring Service (WGMS), an attempt is made here to determine whether there were abrupt decadal-scale changes in annual balance on glaciers in the Tien Shan Mountains. There appears to have been an abrupt change in the mid-1970s; two-thirds of the change was caused by an increase in annual ablation and the other one-third by a decrease in the annual accumulation. Thus, the change was caused mainly by a summer-temperature increase, supplemented by a decrease in annual snowfall. Climate records suggest that this event, in effect, is in response to a shift hi the background state of the coupled Ocean -atmosphere system over the Tropical Pacific during the mid-1970s.
Efficient Photoacoustic Image Synthesis with Deep Learning

Photoacoustic imaging potentially allows for the real-time visualization of functional human tissue parameters such as oxygenation but is subject to a challenging underlying quantification problem. While in silico studies have revealed the great potential of deep learning (DL) methodology in solving this problem, the inherent lack of an efficient gold standard method for model training and validation remains a grand challenge. This work investigates whether DL can be leveraged to accurately and efficiently simulate photon propagation in biological tissue, enabling photoacoustic image synthesis. Our approach is based on estimating the initial pressure distribution of the photoacoustic waves from the underlying optical properties using a back-propagatable neural network trained on synthetic data. In proof-of-concept studies, we validated the performance of two complementary neural network architectures, namely a conventional U-Net-like model and a Fourier Neural Operator (FNO) network. Our in silico validation on multispectral human forearm images shows that DL methods can speed up image generation by a factor of 100 when compared to Monte Carlo simulations with 5×108 photons. While the FNO is slightly more accurate than the U-Net, when compared to Monte Carlo simulations performed with a reduced number of photons (5×106), both neural network architectures achieve equivalent accuracy. In contrast to Monte Carlo simulations, the proposed DL models can be used as inherently differentiable surrogate models in the photoacoustic image synthesis pipeline, allowing for back-propagation of the synthesis error and gradient-based optimization over the entire pipeline. Due to their efficiency, they have the potential to enable large-scale training data generation that can expedite the clinical application of photoacoustic imaging.