Miracle-dz/UniFAR-FTUs huggingface dataset:
Remediation of Uranium in the Hanford Vadose Zone Using Ammonia Gas: FY 2010 Laboratory-Scale Experiments

This investigation is focused on refining an in situ technology for vadose zone remediation of uranium by the addition of ammonia (NH3) gas. Objectives are to: a) refine the technique of ammonia gas treatment of low water content sediments to minimize uranium mobility by changing uranium surface phases (or coat surface phases), b) identify the geochemical changes in uranium surface phases during ammonia gas treatment, c) identify broader geochemical changes that occur in sediment during ammonia gas treatment, and d) predict and test injection of ammonia gas for intermediate-scale systems to identify process interactions that occur at a larger scale and could impact field scale implementation.Overall, NH3 gas treatment of low-water content sediments appears quite effective at decreasing aqueous, adsorbed uranium concentrations. The NH3 gas treatment is also fairly effective for decreasing the mobility of U-carbonate coprecipitates, but shows mixed success for U present in Na-boltwoodite. There are some changes in U-carbonate surface phases that were identified by surface phase analysis, but no changes observed for Na-boltwoodite. It is likely that dissolution of sediment minerals (predominantly montmorillonite, muscovite, kaolinite) under the alkaline conditions created and subsequent precipitation as the pH returns to natural conditions coat some of the uranium surfacemore » phases, although a greater understanding of these processes is needed to predict the long term impact on uranium mobility. Injection of NH3 gas into sediments at low water content (1% to 16% water content) can effectively treat a large area without water addition, so there is little uranium mobilization (i.e., transport over cm or larger scale) during the injection phase. « less
EL REGISTRO MICROPALEONTOLÓGICO DEL SOLUTRENSE EN LA REGIÓN CANTÁBRICA (ESPAÑA): ESTADO DE LA CUESTIÓN The micropaleontological record of the Solutrean in the Cantabrian Region (Spain): state of arts

El presente articulo es una revision de los sitios arqueologicos y paleontologicos con estudios palinologicos y de microvertebrados de cronologia Solutrense de la region cantabrica. Aunque hoy en dia, los estudios paleoambientales son un elemen
Predicting aviation hazards during convective events

Atmospheric convection can result in weather conditions capable of making a pilot lose control of the aircraft. An example of such weather is thunderstorms. This study was made to evaluate weather forecasts for aircraft pilots during days of convective activity. For this purpose, a literature study was conducted to identify the weaknesses of numerical weather prediction models in their handling of convection, and limita-tions of aviation targeted forecast products were addressed. The study also includes remarks and insights received from experienced aviation forecasters on the subject. The study is limited to Sweden and the forecasts made by the Swedish Meteoro-logical and Hydrological Institute (SMHI). Four main results have been found. Firstly, the numerical weather prediction models in use in Sweden today are insufficient for making detailed forecasts of convection. Secondly, the required additional input from human forecasters is restrained by the imperfections of so-called convective indices. Thirdly, convection forecasts issued more than a few hours ahead of time cannot be trusted as being accurate. Finally, the forecast products available to pilots were found to lack valuable information about convective events. It was concluded that pilots cannot access enough information from these forecast products to be able to plan an altogether safe flight through convective weather beforehand. Hence, it is important to improve forecasts of convection for the purpose of enhancing aviation safety.
Comparing the Effect of Monofilament and Braided Suture on Pregnancy Loss Rates in Women Requiring Vaginal Cervical Cerclage

Article information Background: Preterm birth affects 11% of pregnancies and can result in serious complications. Cervical insufficiency is a frequent reason for preterm birth and also can be treated with vaginal cervical cerclage using different types of sutures. Observational studies suggest that monofilament sutures may decrease pregnancy loss compared to braided sutures, but randomized controlled studies are needed to confirm this finding. Aim of the work: The research aims to assess the efficacy of monofilament versus braided sutures in preventing miscarriage for women undergoing vaginal cervical cerclage. Patients and Methods: This trial was done in Obstetrics and Gynecology Department, El-Hussein University Hospital, from January 2020 to November 2022. There were 201 participants in the study. Individuals were monitored in the obstetrics and gynecological clinics at El-Hussein University Hospital, Faculty of Medicine, Al-Azhar University. Females with a singleton pregnancy and a cervical cerclage indicator were split evenly amongst receiving a monofilament or braided suture. Pregnancy loss was the fundamental result; secondary outcomes included maternal and neonatal outcomes. Surgeons were permitted to employ any method they found most effective. Results: No significant variances were present in baseline characteristics, pregnancy and maternal outcomes, and neonatal outcomes between the two study groups. However, the Monofilament suture group had significantly more complications with cerclage removal. Conclusion: Both monofilament and braided sutures are effective and safe procedures with minimal side effects and complications. Although monofilament suture may cause more difficult removal and removal complications, it remains a viable option for treating cervical insufficiency.
Leveraging Exercise is Medicine On Campus Programs to Promote Activity to Equity-Deserving Groups

Despite the well-known benefits of leading an active lifestyle, global adherence to physical activity recommendations is low. Individuals who are from marginalized groups, including racialized populations and those with a low socio-economic status, are more physically inactive compared to those who identify as white or who have a higher income. The differences in physical activity level by socio-demographic characteristics reflect inequitable access to lifestyle resources. Exercise is Medicine On Campus (EIM-OC) is a unique international post-secondary initiative that aims to promote a culture of physical activity and chronic disease prevention and management on university/college campuses and within their local communities. EIM-OC programs currently exist on every continent, with the majority of chapters existing in North America. This provides EIM-OC a unique opportunity to address inequities in physical activity promotion. This commentary provides perspective on traditional EIM-OC program offerings, highlights learnings from the COVID-19 pandemic, and recommends strategies to increase the inclusivity of future physical activity programming.
Automated Catalog Generation using Deep Learning

Automated catalog generation plays a crucial role in e-commerce, retail, and inventory management systems. Object detection holds immense significance within the realm of computer vision, particularly in grocery item recognition. Deep learning techniques have shown remarkable advancements in various domains, including computer vision. In this research, we propose an automated catalog generation framework utilizing deep learning methods. Specifically, we integrate RoboFlow for image annotation and YOLOv7 and object detection algorithms for dataset training and testing. We present a comprehensive methodology for dataset preparation, annotation, training, and evaluation. The proposed framework demonstrates promising results on diverse datasets, including a novel self-generated benchmark dataset. Our model achieves significant accuracy in object detection and annotation, showcasing its potential for efficient and accurate catalog generation. The scalability and adaptability of our framework open avenues for real-world applications in inventory management and e-commerce platforms. This research focuses on the application of deep learning techniques to automate the generation of product catalogs in supermarkets. The project involves annotating a diverse dataset of grocery item images collected from various sources using Roboflow. The images are then processed and trained using the YOLOv7 and object detection algorithms. The results showcase the successful implementation of Roboflow for automated image annotation, enabling accurate and efficient object detection.
Preparation and Evaluation of Controlled-Release Solid Dispersion Granules Containing a Poorly Water-Soluble Drug, Hydrated Silicon Dioxide, and Polyvinylpyrrolidone

The study aim was to develop controlled-release, solid dispersion granules containing a poorly water-soluble drug, Hydrated Silicon Dioxide (HSD), and Polyvinylpyrrolidone (PVP), and to elucidate the mechanism underlyingsustained release from the soliddispersion granules. To achieve this purpose, we used the wet granulation method to prepare the first-release granules containing a poorly water-soluble drug and HSD. Then, the effect of PVP on the dissolution of the poorly water-soluble drug was estimated. Initially, the selection of a binder and contentsof drug and binder were investigated to determine the optimum formulation fora rapidly dissolving granule with HSD. Firstrelease granules containing Nifedipine (NIF) as a poorly water-soluble drug, erythritol as a binder, and HSD were developed. Differential scanning calorimetry confirmed reduced NIF crystallinity in the granules. To investigate the first-release granules’ applicabilityto other drugs, six poorly water-soluble drugs (griseofulvin, indomethacin, ibuprofen, carbamazepine, progesterone, and phenytoin) were prepared. Rapid dissolutionof all tested drugs from the granule with the same NIF formulation was observed. These findings suggest that HSD is useful for improving dissolution ratesof poorly water-soluble drugs insoliddispersion granules. Next, we investigated PVP’s effect on the dissolution of drug from the first-release granules. The effects of PVP on sustained release from the granules containing the seven drugs weredivided into three types: Type 1 was no effect (rapid dissolution), type 2 was a middle effect, and type 3 was a strong effect (sustained release). To elucidate the mechanism underlying sustained release from the solid dispersion granules, the intermolecular interactions between the drugs and HSD or PVP were investigated by Fourier transform infrared spectroscopy. The results suggested that the balance between the interaction of a drug and HSD and the interaction of a drug and PVP is important for sustained release of the drug.
Sensor-guided machining of large-scale CFRP components based on resin transfer molded features

Carbon fiber-reinforced Plastics (CFRP) are a key factor for achieving a carbon-neutral mobility sector due to their lightweight properties. Despite their near-net-shape manufacturing subsequent precision machining is required. In case of large-scale CFRP components, which are characterized by small quantities and low machining volumes, such processes are difficult to operate economically with conventional systems. Robotic systems offer a suitable solution. Their use in machining, however, requires additional measures to compensate for structural system limitations. In addition, individual deviations of the blanks require time-consuming measuring for referencing the machining system. To enable the use of cost-efficient robotic systems and to eliminate unproductive downtime for measuring, the intended manufacturing of CFRP components by Resin Transfer Molding (RTM) offers a new opportunity. RTM allows for the integration of defined features into the molding tool, which are reproduced inverted on the component and can be referenced by subsequent processes. This is utilized with adapted strategies for time-efficient measuring and high-precision machining. Fundamentals for the corresponding feature design as well as the selection of a suitable measuring device are presented. Focusing on laser-based sensors, the relationship between wavelength and (semi-)transparent surfaces is discussed and validated. Besides the metrological detection, production-specific aspects are also taken into account. Based on the gained knowledge, the main aspects of a proper sensor-feature combination are elaborated and prototypically realized. Finally, an outlook is provided on the challenges involved when implementing a robust algorithm for feature detection.
Effects of the Recreational Fee Demonstration Program on backcountry users in Grand Canyon and Everglades National Parks

approved: Rebecca L. Johnson Since the Recreational Fee Demonstration Program was approved in 1996, allowing public land management agencies to collect and retain recreation user fees, several research studies have gathered opinions and attitudes from different groups of recreation users. One particular group, backcountry users of National Parks, had yet to be included. This thesis uses a sample of backcountry users from Grand Canyon and Everglades National Park to determine opinions and attitudes, potential displacement, and visitation responses to increased recreation user fees. Backcountry users at these National Parks were found to be supportive of most recreation user fees, such as entrance and backcountry permit fees. However, this was not always the case; few found parking fees appropriate. The consistent opinion of respondents at both National Parks was that fee revenue should be used to revegetate impacted sites. Most backcountry users found the current price of the permit fees to be "about right. " Potential displacement is often a concern when recreation user fees are implemented. In this thesis, there were few significant demographic differences between samples that had visited before fee implementation and those that had visited after implementation. There were, however, changes in trip characteristics such as mode of transportation and amount of pre-trip planning Three to 13% of the respondents said that they would visit less often in the future because of the Recreational Fee Demonstration Program. These potentially displaced users at Everglades National Park were more likely to be low-income. Potentially displaced users at Grand Canyon National Park were more likely to be non-white, low-income, not working full time, and live closer to the National
The Anti-inflammatory Effect of flaxseed oil on Ligature Induced Periodontitis in Mandibular Molars of Wistar Rats (An Animal Study)

Aim: To evaluate therapeutic anti-inflammatory effect of intraperitoneally injected flaxseed oil in Wister rats exposed to ligature induced periodontitis in mandibular right first molar. Methodolgy: Eighteen male Wister rats were randomized into three groups: group I (control) was supplied with intraperitoneal injection of (3 ml/Kg) of saline each other day. Periodontitis was induced for group II, III by ligature placement under general anesthesia. After four weeks, group II was injected with saline intraperitoneally (3ml/kg) each other day, for 2 weeks, while group III was injected with flaxseed oil intraperitoneally (3ml/kg) each other day, for 2 weeks. Results: Histolopathological examination of group I showed normal architecture of both the periodontal ligament and alveolar bone tissues. While group II (untreated) revealed disruption of periodontal ligament fibers, inflammatory cell infiltration and marked alveolar bone resorption. Group III (treated group) showed re-organization of the periodontal ligaments, less inflammatory cells infiltration, regular bone surface lined by osteoblasts and obvious reversal lines were recognized denoting new bone formation. The quantitative real-time polymerase chain reaction results of Interlekin-10, transforming growth factor-β gene expression displayed a significant decrease in their expression in group II, while increase their expression in group III. Alternatively, osteopontin gene expression displayed a significant increase in its expression in group II and decrease its expression in group III. Conclusion: In a rat model, intraperitoneal injection of flaxseed oil aids in resolution of mechanically induced periodontal tissue inflammation and accelerates healing process.
SLAM algorithm based on natural environment and reflective column information

Aiming at the stability and accuracy of the mapping and positioning of the Automated Guided Vehicle (AGV) in longdistance driving and complex environments , a post-processing method using graph optimization and filtering is proposed. A terminal optimization algorithm, when this algorithm is optimized, it will give priority to extracting the reflective column information. When the reflective column information is not detected at the front end of SLAM , the system will use the conventional graph optimization algorithm for positioning and mapping. After detecting the reflective column and obtaining the coordinates of the reflective column, the system will switch to the extended Kalman filter. (Extended Kalman Filter, EKF ) algorithm to locate the AGV . It has been verified by experiments that when the system travels long distances through special scenes that are difficult to locate, such as open spaces, complex environments, or frequent changes in the environment, the positioning accuracy and robustness of the SLAM algorithm that alternately uses natural environment information and reflective column information can achieve certain improvements.
The Role of Immune Cells in Liver Regeneration

The liver is the only organ that can regenerate and regain its original tissue-to-body weight ratio within a short period of time after tissue loss. Insufficient liver regeneration in patients after partial hepatectomy or liver transplantation with partial liver grafts often leads to post-hepatectomy liver failure or small-for-size syndrome, respectively. Enhancing liver regeneration after liver injury might improve outcomes and increase patient survival. Liver regeneration comprises hepatocyte proliferation, and hepatic progenitor cell expansion and differentiation into hepatocytes. The immune system is intensively involved in liver regeneration. The current review provides a comprehensive overview of the diverse roles played by immune cells in liver regeneration. Macrophages, neutrophils, eosinophils, basophils, mast cells, platelets, dendritic cells, type 1 innate lymphoid cells, B cells, and T cells are implicated in promoting liver regeneration, while natural killer cells and overactivated natural killer T cells are supposed to inhibit hepatocyte proliferation. We also highlight the predominant underlying mechanisms mediated by immune cells, which may contribute to the development of novel strategies for promoting liver regeneration in patients with liver diseases.
Privacy-preserving continual learning methods for medical image classification: a comparative analysis

Background The implementation of deep learning models for medical image classification poses significant challenges, including gradual performance degradation and limited adaptability to new diseases. However, frequent retraining of models is unfeasible and raises concerns about healthcare privacy due to the retention of prior patient data. To address these issues, this study investigated privacy-preserving continual learning methods as an alternative solution. Methods We evaluated twelve privacy-preserving non-storage continual learning algorithms based deep learning models for classifying retinal diseases from public optical coherence tomography (OCT) images, in a class-incremental learning scenario. The OCT dataset comprises 108,309 OCT images. Its classes include normal (47.21%), drusen (7.96%), choroidal neovascularization (CNV) (34.35%), and diabetic macular edema (DME) (10.48%). Each class consisted of 250 testing images. For continuous training, the first task involved CNV and normal classes, the second task focused on DME class, and the third task included drusen class. All selected algorithms were further experimented with different training sequence combinations. The final model's average class accuracy was measured. The performance of the joint model obtained through retraining and the original finetune model without continual learning algorithms were compared. Additionally, a publicly available medical dataset for colon cancer detection based on histology slides was selected as a proof of concept, while the CIFAR10 dataset was included as the continual learning benchmark. Results Among the continual learning algorithms, Brain-inspired-replay (BIR) outperformed the others in the continual learning-based classification of retinal diseases from OCT images, achieving an accuracy of 62.00% (95% confidence interval: 59.36-64.64%), with consistent top performance observed in different training sequences. For colon cancer histology classification, Efficient Feature Transformations (EFT) attained the highest accuracy of 66.82% (95% confidence interval: 64.23-69.42%). In comparison, the joint model achieved accuracies of 90.76% and 89.28%, respectively. The finetune model demonstrated catastrophic forgetting in both datasets. Conclusion Although the joint retraining model exhibited superior performance, continual learning holds promise in mitigating catastrophic forgetting and facilitating continual model updates while preserving privacy in healthcare deep learning models. Thus, it presents a highly promising solution for the long-term clinical deployment of such models.