Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficacy of calcium sulfate dihydrate as a bone graft substitute in odontogenic cystic defects of jaws following enucleation: A clinical study

ABSTRACT Background: The treatment of osseous bone defects created following enucleation of a cyst is an arduous challenge. Autogenous bone grafts despite being the gold standard have various drawbacks such as donor site morbidity, limited availability of bone graft, and increased operative time. Hence, there are various bone grafts which are being investigated which could overcome the limitations of autografts. Thus, this study was conducted to evaluate the efficacy of calcium sulfate (CS), a bone graft substitute, for spontaneous bone regeneration of cystic defects. Objectives: The purpose of this study is to evaluate bone formation in odontogenic cystic defects following enucleation and reconstruction with bone graft substitute by three-dimensional radiographic and clinical evaluation. Methodology: A total of twenty patients diagnosed with odontogenic cysts were randomly divided into two groups, out of which the study group had undergone enucleation with bone grafting (tobramycin-impregnated CS dihydrate) and the control group had undergone enucleation without bone grafting. The patients were evaluated clinically and radiographically at the 1st, 3rd, 6th, and 12th months postoperatively. Results: There was no bone formation observed at 1 month postoperative in both the groups. There was a statistically significant higher bone defect reduction observed radiologically on orthopantomogram and computed tomography scan in the study group than the control group at the 3rd, 6th, and 12th months postoperative. The rate of reduction in cystic volume of the study group at the 12th month was 94.4% and in the control group was 37.16%. Conclusion: Immediate grafting of cystic cavity can avoid complications such as pathological fracture due to less bone support, delayed healing, etc., The utilization of a graft with a property of inducing rapid bone formation should be taken into consideration. The use of CS as a grafting material accelerated the rate of bone regeneration in the cystic defects, with minimal complications.
Repurposing Approved Drugs for Sarcopenia Based on Transcriptomics Data in Humans

Sarcopenia, characterized by age-related loss of muscle mass, strength, and decreased physical performance, is a growing public health challenge amid the rapidly ageing population. As there are no approved drugs that target sarcopenia, it has become increasingly urgent to identify promising pharmacological interventions. In this study, we conducted an integrative drug repurposing analysis utilizing three distinct approaches. Firstly, we analyzed skeletal muscle transcriptomic sequencing data in humans and mice using gene differential expression analysis, weighted gene co-expression analysis, and gene set enrichment analysis. Subsequently, we employed gene expression profile similarity assessment, hub gene expression reversal, and disease-related pathway enrichment to identify and repurpose candidate drugs, followed by the integration of findings with rank aggregation algorithms. Vorinostat, the top-ranking drug, was also validated in an in vitro study, which demonstrated its efficacy in promoting muscle fiber formation. Although still requiring further validation in animal models and human clinical trials, these results suggest a promising drug repurposing prospect in the treatment and prevention of sarcopenia.
Estimating and testing selection: the two-alleles, genic selection diffusion model

The estimation, and testing for the presence, of a selective advantage of one allele over another is considered. It is assumed that a population's allele frequencies are known from some initial time until fixation of one or other allele occurs. The statistics needed to perform the estimation and testing are the heterozygosity of the population summed over all generations, and the observation of which allele fixes. It is shown that certain asymptotic probability distributions arise which are similar to those proved by Brown and Hewitt for statistical inference from diffusion processes, but their results assumed that the diffusion had a stationary density which is not the case for alleles which fix. The genetic diffusion may be transformed to Brownian motion with constant drift, and the inference questions concerning selection can be transformed to questions about the first exit of a Brownian motion from an interval. It is thus possible to construct significance tests, and to calculate the power of those tests, for detecting selection.
Creation and survival of autoionizing states in strong laser fields

Very sharp, low-energy structures observed in photoelectron spectra reveal the population of autoionizing states in krypton and argon in strong laser fields over a large range of different wavelengths. The energies of the electrons, emitted by autoionization in a field-free environment, provide direct information about the spectrum of states involved. Despite their ability to resist ionization by the populating laser pulse, we demonstrate the possibility to promote the excited electrons into the continuum by subsequent absorption of a single photon. Thus, applying a classical pump-probe scheme, we are able to manipulate the autoionization contribution on a picosecond time scale. Different scenarios for the creation of autoionizing states in strong laser fields are discussed.
Algorithms for bicriteria minimization in the permutation flow shop scheduling problem

This paper presents two bi-objective simulated annealing procedures to deal with the classical permutation flow shop scheduling problem considering the makespan and the total completion time as criteria. The proposed methods are based on multi-objective simulated annealing techniques combined with constructive and heuristic algorithms. A computational experiment has been carried out and different metrics have been computed to check various attributes of each method. For all the tested instances a net set of potentially efficient schedules has been obtained and compared with previously published results. Results indicate that the proposed algorithms provide efficient solutions with little computational effort which can serve as input for interactive procedures.
Estimation of Arctic sea ice thickness from CryoSat-2 altimetry data

ABSTRACT Arctic sea ice change is one of the critical factors affecting the global climate environment; hence, it is crucial to obtain sea ice thickness with high accuracy while studying polar and global climate change. In the process of using altimetry data to estimate sea ice thickness, the mean sea surface height will bring greater uncertainty to the extraction of sea ice freeboard, which will affect the accuracy of sea ice thickness. Also, the influence of snow cover on radar signal penetration will bring greater uncertainty to sea ice thickness. In this paper, we present a processing chain for sea ice thickness estimation. First, we compare the effect of four different MSS models on the freeboard estimation. Then, considering the incomplete penetration of radar signals and the different speeds of radar signals penetrating the snow layer and the vacuum, the traditional sea ice thickness model is optimized to obtain the sea ice thickness. Compared with the Operation IceBridge (OIB) sea ice thickness, the accuracy of sea ice thickness obtained by the optimized model is better than 0.350 m, with a root mean square error of 0.260 m and a mean bias of 0.048 m. The comparison results show that the combination of the latest DTU18 MSS model and sea ice thickness optimization model effectively improve the accuracy of sea ice thickness.
Introgression of Heterotic Genomic Segments from Brassica carinata into Brassica juncea for Enhancing Productivity

Interspecific hybridization resulted in the creation of B. juncea introgression lines (ILs) generated from B. carinata with increased productivity and adaptability. Forty ILs were crossed with their respective B. juncea recipient parents to generate introgression line hybrids (ILHs) and the common tester (SEJ 8) was used to generate test hybrids (THs). Mid-parent heterosis in ILHs and standard heterosis in THs were calculated for eight yield and yield-related traits. Heterotic genomic regions were dissected using ten ILs with significant mid-parent heterosis in ILHs and standard heterosis in THs for seed yield. A high level of heterosis for seed yield was contributed by 1000 seed weight (13.48%) in D31_ILHs and by total siliquae/plant (14.01%) and siliqua length (10.56%) in PM30_ILHs. The heterotic ILs of DRMRIJ 31 and Pusa Mustard 30 were examined using polymorphic SNPs between the parents, and a total of 254 and 335 introgressed heterotic segments were identified, respectively. This investigation discovered potential genes, viz., PUB10, glutathione S transferase, TT4, SGT, FLA3, AP2/ERF, SANT4, MYB, and UDP-glucosyl transferase 73B3 that were previously reported to regulate yield-related traits. The heterozygosity of the FLA3 gene significantly improved siliqua length and seeds per siliqua in ILHs of Pusa Mustard 30. This research proved that interspecific hybridization is an effective means of increasing the diversity of cultivated species by introducing new genetic variants and improving the level of heterosis.
Implementing a Digital Depression Prevention Program in Australian Secondary Schools: Cross-Sectional Qualitative Study

Background Depression is common during adolescence and is associated with adverse educational, employment, and health outcomes in later life. Digital programs are increasingly being implemented in schools to improve and protect adolescent mental health. Although digital depression prevention programs can be effective, there is limited knowledge about how contextual factors influence real-world delivery at scale in schools. Objective The purpose of this study was to examine the contextual factors that influence the implementation of the Future Proofing Program (FPP) from the perspectives of school staff. The FPP is a 2-arm hybrid type 1 effectiveness-implementation trial evaluating whether depression can be prevented at scale in schools, using an evidence-based smartphone app delivered universally to year 8 students (13-14 years of age). Methods Qualitative interviews were conducted with 23 staff from 20 schools in New South Wales, Australia, who assisted with the implementation of the FPP. The interviews were guided by our theory-driven logic model. Reflexive thematic analysis, using both deductive and inductive coding, was used to analyze responses. Results Staff perceived the FPP as a novel (“innovative approach”) and appropriate way to address an unmet need within schools (“right place at the right time”). Active leadership and counselor involvement were critical for planning and engaging; teamwork, communication, and staff capacity were critical for execution (“ways of working within schools”). Low student engagement and staffing availability were identified as barriers for future adoption and implementation by schools (“reflecting on past experiences”). Conclusions Four superordinate themes pertaining to the program, implementation processes, and implementation barriers were identified from qualitative responses by school staff. On the basis of our findings, we proposed a select set of recommendations for future implementation of digital prevention programs delivered at scale in schools. These recommendations were designed to facilitate an organizational change and help staff to implement digital mental health programs within their schools. International Registered Report Identifier (IRRID) RR2-10.1136/bmjopen-2020-042133
ROBUSTNESS ANALYSIS AND DESIGN OF PID CONTROL SYSTEMS

The paper analyzed the robustness of PID control systems widely used in process control,gave a neces- sary condition for robust stability and pointed out the limitation of PID regulators.The paper proposed a method for choosing PID parameters throuth constrained optimization,which gives consideration to both performance and robustness.A function of model uncertainty is used to design a robust control system Which is stable within the prescribed region of variations of transfer function.
The radio structure of NGC 1275

Les images VLA et MERLIN a grande etendue dynamique sont presentees pour la radiosource 3C 84 associee avec la galaxie elliptique geante NGC 1275, aux longueurs d'onde 18, 22, 90, et 199 cm avec des resolutions angulaires s'etendant de 0.3 a 40 secondes d'arc. Les conclusions soutiennent que : (1) l'emission radio dans les 30 secondes d'arc centrales revele l'existence d'une emission collimatee le long de PA ∼ 160°; (2) l'emission collimate existe egalement vers le nord dans PA ∼ 340°; (3) il n'y a pas d'absorption libre-libre vis-a-vis de la structure radio etendue; (4) 3C 84 possede une structure radio Fanaroff-Riley de classe I; (5) des asymetries significatives entre la structure radio au nord et au sud existent dans cette source.
Relevant Choices Affecting the Fatigue Analysis of Ni-Ti Endovascular Devices

Ni-Ti alloys are widely used for biomedical applications due to their superelastic properties, which are especially convenient for endovascular devices that require minimally invasive insertion and durable effects, such as peripheral/carotid stents and valve frames. After crimping and deployment, stents undergo millions of cyclic loads imposed by heart/neck/leg movements, causing fatigue failure and device fracture that can lead to possibly severe consequences for the patient. Standard regulations require experimental testing for the preclinical assessment of such devices, which can be coupled with numerical modeling to reduce the time and costs of such campaigns and to obtain more information regarding the local state of stress and strain in the device. In this frame, this review aimed to enlighten the relevant choices that can affect the outcome of the fatigue analysis of Ni-Ti devices, both from experimental and numerical perspectives.
Analysis of stress, attention, interest, and engagement in onsite and online higher education: A neurotechnological study

The aim of this work is to register and analyse, using neurotechnology, in onsite onsite and online university educational context, the effect on relevant variables in the learning process. This represents an innovation in the current academic literature in this field. In this study, neuroscience technology has been used to measure the cognitive processing of stimuli designed for an academic experience in a university master's degree class. The neurotechnologies employed were galvanic skin response (GSR), electroencephalography (EEG) and eye tracking. After the analysis of the brain recordings, based on attention, interest, stress and engagement in an onsite educational context and their comparative analysis with the online monitoring, the results indicated that the levels of emotional intensity of the students who followed the class in person were higher than those who attended online. At the same time, the values of positive brain activity (attention, interest and engagement) were higher in the onsite group, and the negative variable stress was also higher, which could be explained by the fact that the online students did not activate the camera. The brain recordings of students who were distance learning show less interest and attention, as well as less emotional intensity, demonstrating that distance (online) learning is less effective than classroom learning, in terms of brain signals, for a theoretical university master's degree class. Este trabajo tiene como objetivo registrar y analizar, mediante el uso de neurotecnología, en un contexto formativo universitario presencial y online, el efecto que tiene en variables relevantes en el proceso de aprendizaje, lo cual supone una innovación en la literatura. En este estudio se ha empleado tecnología de neurociencia para medir el procesamiento cognitivo de los estímulos diseñados para una experiencia académica de una clase de máster universitario. Las neurotecnologías empleadas han sido la respuesta galvánica de la piel (GSR), la electroencefalografía (EEG) y el seguimiento ocular. Tras el análisis de los registros cerebrales, basados en la atención, interés, estrés y conexión emocional (engagement), en un contexto educativo presencial y su análisis comparativo con el seguimiento online, los resultados indicaron que los niveles de intensidad emocional de los alumnos que siguieron la clase de forma presencial son más elevados que aquellos que asistieron de forma online. A su vez, los valores de actividad cerebral positiva (atención, interés y engagement) son superiores en el grupo de asistencia presencial, siendo la variable negativa estrés también superior, pudiendo justificarse debido a que los alumnos conectados online no activaban la cámara. Los registros cerebrales de los alumnos que asisten a distancia muestran menor interés y atención, así como una menor intensidad emocional, por lo que el aprendizaje a distancia (online) es menos efectivo, a efectos de señales cerebrales, que la enseñanza en el aula, para una clase teórica de máster universitario.
Nutritional Strategies to Improve Meat Quality and Composition in the Challenging Conditions of Broiler Production: A Review

Simple Summary Intense genetic selection and improvements in nutrient programs have enhanced the growth performance, feed efficiency, and meat yield of broiler chickens. The quality characteristics and nutrient composition of poultry meat are also crucial factors in poultry production. Many challenging conditions, including fast growth, pathogen infection, high rearing temperature, and feed contamination, can negatively influence poultry meat quality and composition. Studies have demonstrated that modulating the nutrient composition of feed and supplementing bioactive compounds, including vitamins, probiotics, prebiotics, exogenous enzymes, polyphenol compounds, and organic acids, have positively influenced the meat quality and body composition of broiler chickens. Abstract Poultry meat is becoming one of the most important animal protein sources for human beings in terms of health benefits, cost, and production efficiency. Effective genetic selection and nutritional programs have dramatically increased meat yield and broiler production efficiency. However, modern practices in broiler production result in unfavorable meat quality and body composition due to a diverse range of challenging conditions, including bacterial and parasitic infection, heat stress, and the consumption of mycotoxin and oxidized oils. Numerous studies have demonstrated that appropriate nutritional interventions have improved the meat quality and body composition of broiler chickens. Modulating nutritional composition [e.g., energy and crude protein (CP) levels] and amino acids (AA) levels has altered the meat quality and body composition of broiler chickens. The supplementation of bioactive compounds, such as vitamins, probiotics, prebiotics, exogenous enzymes, plant polyphenol compounds, and organic acids, has improved meat quality and changed the body composition of broiler chickens.
Estimation for non‐negative time series with heavy‐tail innovations

For moving average processes where the coefficients are non‐negative and the innovations are positive random variables with a regularly varying tail at infinity, we provide estimates for the coefficients based on the ratio of two sample values chosen with respect to an extreme value criteria. We then apply this result to obtain estimates for the parameters of non‐negative ARMA models. Weak convergence results for the joint distribution of our estimates are established and a simulation study is provided to examine the small sample size behaviour of these estimates.
A robotic approach for crack detection through the integration of cameras and LiDARs

Structural health monitoring is crucial for ensuring the safety of civil infrastructure, and crack detection is an essential component of this process. Cameras provide high-resolution images of the structure’s surface, which can be analyzed to detect and locate cracks. LiDAR sensors use laser beams to scan the surface of the structure and produce detailed 3D point clouds that can be used to detect cracks and measure their dimensions. The proposed approach aims to improve the accuracy and efficiency of crack detection in SHM by integrating the complementary strengths of cameras and LiDARs in a simulation environment. The approach involves the use of an intelligent algorithm that can automatically fuse the data from the cameras and LiDARs to produce a more comprehensive and accurate representation of surface cracks. The algorithm uses a machine learning-based crack detection technique that can accurately identify and locate cracks in real-time. Furthermore, a depth camera is used to provide a denser point cloud than LiDAR of the crack. The integration of cameras and LiDARs for crack detection in SHM offers several advantages, such as improved accuracy, faster data acquisition, and reduced costs compared to traditional methods. The proposed approach addresses the challenges of data fusion, image processing, and intelligent algorithm development by offering a novel solution that leverages the strengths of both cameras and LiDARs. The findings of this study suggest that the proposed approach can significantly enhance the capabilities of SHM for crack detection. The approach offers a more accurate and efficient way of detecting cracks in real-time, which can help prevent further damage and ensure the safety of civil infrastructure.
Overcoming the Fibrotic Fortress in Pancreatic Ductal Adenocarcinoma: Challenges and Opportunities

Simple Summary Pancreatic ductal adenocarcinoma (PDAC) is the most common form of pancreatic tumours, representing greater than 90% of all diagnosed cases of pancreatic cancer. PDAC has the lowest 5-year survival rate of all tumour malignancies with less than 9% patient survival. A unique feature of PDAC tumours is the presence of a dense fibrotic fortress that creates a physical barrier around the cancer cells, thus resulting in a reduced penetrability of drugs and a ‘sanctuary’ in which cancer cells thrive, termed desmoplasia. Extensive desmoplasia in the PDAC tumour microenvironment (TME) is a crucial factor that influences PDAC development, progression, metastasis, and resistance to treatment. This review will focus on the role of the TME in PDAC, current treatments for PDAC, and a reflection on past and current clinical trials targeting components of the TME in PDAC. Abstract An overabundance of desmoplasia in the tumour microenvironment (TME) is one of the defining features that influences pancreatic ductal adenocarcinoma (PDAC) development, progression, metastasis, and treatment resistance. Desmoplasia is characterised by the recruitment and activation of fibroblasts, heightened extracellular matrix deposition (ECM) and reduced blood supply, as well as increased inflammation through an influx of inflammatory cells and cytokines, creating an intrinsically immunosuppressive TME with low immunogenic potential. Herein, we review the development of PDAC, the drivers that initiate and/or sustain the progression of the disease and the complex and interwoven nature of the cellular and acellular components that come together to make PDAC one of the most aggressive and difficult to treat cancers. We review the challenges in delivering drugs into the fortress of PDAC tumours in concentrations that are therapeutic due to the presence of a highly fibrotic and immunosuppressive TME. Taken together, we present further support for continued/renewed efforts focusing on aspects of the extremely dense and complex TME of PDAC to improve the efficacy of therapy for better patient outcomes.