Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparative Evaluation of the Anesthetic Efficacy of Needle-Free Anesthesia and Conventional Anesthesia in Patients With Symptomatic Irreversible Pulpitis: A Randomized Clinical Trial

Introduction Pain is the primary reason for which most of the patients seek endodontic treatment. Local anesthesia is considered to be the most important step in the procedure to reduce the pain. However, the majority of the patients do not cooperate due to the fear of syringe anesthesia. The aim of this clinical trial was to compare the anesthetic efficacy of needle-free anesthesia and conventional anesthesia in patients with symptomatic irreversible pulpitis undergoing root canal therapy. Materials and methods A total of 54 patients were enrolled in the study, and the treatment was administered by a single operator. The initial assessment of vitality included cold testing, heat testing, and electric pulp testing. Preoperative pain was assessed using the Visual Analog Scale (VAS) before the administration of anesthesia. Local anesthesia was administered according to the group assigned: Group 1 (conventional anesthesia) and Group 2 (needle-free anesthesia). The pain was assessed during the administration of anesthesia. Following the administration of anesthesia, the vitality of the tooth was evaluated using cold testing, heat testing, and electric pulp testing. Subsequently, the tooth was isolated with a rubber dam, and the access cavity was prepared. The pain was assessed during access cavity preparation and during the first file insertion. Working length was determined using an apex locator (Root ZX Mini, J Morita, Saitama, Japan) and was confirmed using intraoral periapical radiographs. Later on, further treatment was carried out. Results A total of 54 participants were included in this clinical trial. There was no significant difference in mean age distribution between the two groups (p=0.852). Considering the frequency distribution of gender, there was no significant difference; however, Group 1 had more female participants (59.3%) compared to Group 2 (33.3%). There was a significant reduction in the mean pain score in Group 2 compared to Group 1 during the delivery of anesthetic agents (p=0.000). Conclusion Needle-free anesthesia proves to be equally effective as the conventional syringe system in patients experiencing symptomatic irreversible pulpitis undergoing root canal treatment. However, it is noteworthy that patients exhibited greater comfort levels with needle-free anesthesia systems specifically during the administration of the anesthetic solution.
Prediction-Based MIMO Control of a Multiport Magnetic-Coupled Energy Router

Multiport power converters are important for energy routing in renewable energy applications. Particularly, magnetic-coupled multiport converters are especially advantageous in terms of galvanic isolation and reduced number of magnetic components. They also enable highly integrated and modularized circuit designs. Meanwhile, their multiple-input and multiple-output (MIMO) nature complicates the control, particularly with a possibly large number of ports for routing purposes. Unlike the existing single-input and single-output (SISO) controls, this article develops a continuous-control-set model predictive control (MPC)-based MIMO control scheme that improves the dynamic performance of the multiport power converters, minimizes interference among different ports, and simplifies the controller design process. The aspects of state-space MIMO modeling, optimization problem definition and solution, and necessary modifications are systematically discussed for practical real-time implementation, especially on low-cost microcontroller units (MCUs). Finally, the developed MPC-based MIMO control is experimentally validated by a prototype eight-port energy router (800 W maximum power) exhibiting superior dynamic responses and a high system efficiency above 94% over a wide power range.
Performance Analysis of UAV RF/FSO Co-Operative Communication Network with Co-Channel Interference

The unmanned aerial vehicle (UAV) communication network has emerged as a promising paradigm capable of independent operation and as a relay to enhance communication coverage and efficiency. However, densely distributed terrestrial base stations with shared communication frequencies inevitably generate co-channel interference (CCI). The interference effect can be effectively eliminated by implementing free-space optical (FSO) communication in the UAV communication network. This paper proposes a solution for the UAV communication network to address interference effectively, specifically by employing a hybrid millimeter-wave radio frequency (RF)/FSO communication system. The RF links serve as the primary means of communication, while the FSO links act as a backup means of communication in the case of CCI. The exact outage probability (OP) and average symbol error rate (SER) expressions are derived for the hybrid RF/FSO communication network. The decision to switch between them depends on the signal-to-interference-plus-noise ratio (SINR). Furthermore, the SINR switching threshold value, which satisfies the target SER, has been calculated numerically for the proposed model. Simulation results indicate that the proposed network notably enhances the OP and attains a signal-to-noise ratio gain of approximately 4.6 dB in the average SER, particularly in scenarios where the RF links are subjected to severe interference or adverse weather conditions, as opposed to a pure RF communication network.
Possibility of the modelling of electricity production from hydropower

In hydropower plants benefits depends on available flow. The paper presents a hybrid model for forecasting the operation of a hydropower plant, including the production of electricity. The possibility of mathematical modeling was chosen to show connections between observed in the past hydrological conditions (available flow) and energy deliver in the future. The available flow which is not enough for start turbines was forecasting by logistic regression model. The opposite situation when the flow starts turbine to produce energy, regression models (the support vector machines SVM, random forest RF, k nearest neighbour k-NN) were used. Results from hybrid model were compared with chosen data-mining methods. The possibility of forecasting of the length of periods when hydropower plant will be working could be very useful. It provides the prognosis of energy value which could be produced from hydropower plant. From the investors’ point of view the economic justification for the execution of the project based on the future energy producing could be a main criteria to realize or buy/sell hydropower plant. Also the secondary importance could be a possibility of planning review and maintenance work. Knowledge of power plant working periods could be a base for assessing a potential production from hydropower plant.
Assessing the Effectiveness of Coastal Foredune Barriers in Reducing Hurricane Washover Sedimentation

ABSTRACT Williams, H. , 2018. Assessing the effectiveness of coastal foredune barriers in reducing hurricane washover sedimentation. This study tests the effectiveness of physical barriers in blocking or reducing washover sedimentation in coastal marshes. It is widely assumed that natural and artificial physical barriers, such as foredunes and roads, block or reduce storm overwash. However, there appears to be little documented assessment of this effect. This topic has gained significance recently because of concerns over sea-level rise induced by global warming creating a larger potential threat from storm overwash. Nearshore physical barriers act to protect populations and infrastructure farther inland from storm surge, but they may also reduce sediment delivery to coastal marshlands, slowing their vertical accretion and contributing to their submergence by rising sea level. Consequently, there is a critical need for more information on the effect of physical barriers on marsh sedimentation. Washover sediment beds were examined along two transects across marshes in McFaddin National Wildlife Refuge in southeastern Texas, one in the lee of a higher and wider foredune barrier and one where foredunes are lower and narrower. Washover sediment beds deposited by Hurricanes Rita (2005) and Ike (2008) were found on both transects. Comparison of washover sedimentation along the two transects showed an average 40% reduction in sediment volume and an average reduction in inland extent of deposits of 505 m in the lee of the higher and wider barrier. These results show that even relatively subtle increases in barrier dimensions can cause substantial reductions in the magnitude of washover sedimentation in marshes. These findings have implications for paleotempestology studies that use the magnitude of washover sedimentation in the lee of dynamic coastal barriers as geologic proxies of storm intensity. Coastal management agencies contemplating the use of physical barriers to block storm surge should take into consideration the impact of such barriers on the sustainability of coastal marshes faced with rising sea level.
Phyto-Mediated Green Synthesis of Silver Nanoparticles Using an Aqueous Leaf Extract of Momordica cymbalaria: Antioxidant, Cytotoxic, Antibacterial, and Photocatalytic Properties

In this study, we biosynthesized the stable silver nanoparticles (AgNPs) from Momordica cymbalaria leaves to evaluate their antioxidant, antibacterial, cytotoxic, and photocatalytic properties. Initially, we screened the bioactive compounds from M. cymbalaria extract using GC-MS. The biosynthesis of Mc-AgNPs was confirmed using instruments, such as UV-visible spectroscopy FT-IR, XRD, SEM with EDX, and HR-TEM analyses. The UV-visible spectrum indicated absorbance at 425 nm. The crystallite size of the M. cymbalaria-stabilized nanoparticles was determined to be 20.14 nm. The morphology and size of the synthesized Mc-AgNPs were confirmed via SEM-EDX and HR-TEM analyses, with a size range from 16 to 22 nm. The synthesized Mc-AgNPs exhibited a photocatalytic yield of 60%. The biosynthesized Mc-AgNPs demonstrated strong antioxidant properties and prominent antibacterial activity against human pathogenic bacteria. The cytotoxicity study revealed that Mc-AgNPs were effective against MCF-7 cells in a dose-dependent manner. The recognized bioactivities confirm that the synthesized Mc-AgNPs act as effective catalysts in oxidation and serve as potent antioxidant, anticancer, and antibacterial agents.
3-D Spatial Optical Crosstalk Characterization of Mini-LED Array by Hyperspectral Imaging and Spectrum-Based Ray Tracing

In micro-/mini-light-emitting diode (Micro-/ Mini-LED) displays, optical crosstalk among chips is a critical issue. The precise optical crosstalk characterization of LED arrays is essential for designing high-contrast ratio optical crosstalk-free displays. In this study, we proposed a spectrum-based Monte Carlo ray tracing model to analyze the 3-D spatial optical crosstalk of the RGB mini-LED array. The model is based on the 2-D surface spectral distribution acquired by microscopic hyperspectral imaging (<inline-formula> <tex-math notation="LaTeX">$\mu $ </tex-math></inline-formula>-HSI) and validated by a spectral goniometer with a maximum deviation of less than 8.61%. Combining with a microintegrating sphere array (<inline-formula> <tex-math notation="LaTeX">$\mu $ </tex-math></inline-formula>-ISA), the 2-D optical crosstalk-free spectral distribution of the RGB Mini-LED array is imported to create the ray tracing model. In addition to the conventional light intensity distribution, color purity distribution and optical crosstalk at arbitrary spatial position can also be deduced. A pinhole-masked fiber spectrometer is used to verify the accuracy of the Monte Carlo ray tracing with a maximum deviation of less than 8.30%. The results indicate the great potential of spectrum-based Monte Carlo ray tracing in the designing of high-resolution microsized LED displays.
Optimal Adaptive Fractional Order Integral Sliding Mode Controller-Energy Management Strategy for Electric Vehicles Based on Bald Eagle Search Algorithm

This research presents an optimal energy management system (EMS) for a lithium-ion battery-supercapacitor hybrid storage system used to power an electric vehicle. The storage systems are connected in parallel to the DC bus by bidirectional DC-DC converters and feed a synchronous reluctance motor through an inverter. The proposed energy management strategy is built on the idea to take full benefits of two combined methods: the bald eagle search algorithm and fractional order integral sliding mode control. To evaluate the effectiveness of the suggested optimal energy management strategy, an urban dynamometer driving schedule (UDDS) driving cycle is considered. The obtained results are compared to a classical fractional order integral sliding mode control-based energy management strategy in terms of voltage ripples, overshoots, and battery final state of charge. The ultimate results approve the ability of the proposed energy management system to enhance the power quality and enhance battery power consumption at the same time. Comprehensive processor-in-the-loop (PIL) cosimulations were conducted on the electric vehicle using the C2000 launchxl-f28379d digital signal processing (DSP) board to assess the practicability and effectiveness of the proposed EMS.
Self-healing and shape-memory polymers based on cellulose acetate matrix

ABSTRACT The creation of self-healing polymers with superior strength and stretchability from biodegradable materials is attracting increasing attention. In this study, we synthesized new biomass-derived cellulose acetate (CA) derivatives by ring-opening graft polymerization of δ-valerolactone followed by the introduction of ureidopyrimidinone (Upy) groups in the polymer side chains. Due to the semicrystalline aliphatic characteristics of the side chain poly(δ-valerolactone) (PVL) and quadruple hydrogen bonds formed by the Upy groups, the stretchability of the resulting polymers was significantly enhanced. Moreover, the shape memory ability and self-healing property (58.3% of self-healing efficiency) were successfully imparted to the polymer. This study demonstrates the great significance of using biomass sources to create self-healing polymers.
Flower‐visitor and pollen‐load data provide complementary insight into species and individual network roles

Most animal pollination results from plant–insect interactions, but how we perceive these interactions may differ with the sampling method adopted. The two most common methods are observations of visits by pollinators to plants and observations of pollen loads carried by insects. Each method could favour the detection of different species and interactions, and pollen load observations typically reveal more interactions per individual insect than visit observations. Moreover, while observations concern plant and insect individuals, networks are frequently analysed at the level of species. Although networks constructed using visitation and pollen‐load data have occasionally been compared in relatively specialised, bee‐dominated systems, it is not known how sampling methodology will affect our perception of how species (and individuals within species) interact in a more generalist system. Here we use a Diptera‐dominated high‐Arctic plant–insect community to explore how sampling approach shapes several measures of species' interactions (focusing on specialisation), and what we can learn about how the interactions of individuals relate to those of species. We found that species degrees, interaction strengths, and species motif roles were significantly correlated across the two method‐specific versions of the network. However, absolute differences in degrees and motif roles were greater than could be explained by the greater number of interactions per individual provided by the pollen‐load data. Thus, despite the correlations between species roles in networks built using visitation and pollen‐load data, we infer that these two perspectives yield fundamentally different summaries of the ways species fit into their communities. Further, individuals' roles generally predicted the species' overall role, but high variability among individuals means that species' roles cannot be used to predict those of particular individuals. These findings emphasize the importance of adopting a dual perspective on bipartite networks, as based on the different information inherent in insect visits and pollen loads.
Impact of Urban Growth and Changes in Land Use on River Flood Hazard in Villahermosa, Tabasco (Mexico)

The city of Villahermosa, a logistical center in the State of Tabasco’s economy, is affected by recurrent river floods. In this study, we analyzed the impact of two factors that are the most probable causes of this increase in flood hazard: changes in land use in the hydrological catchments upstream of the city, and the uncontrolled urbanization of the floodplains adjacent to the main river channels. Flood discharges for different return periods were evaluated, considering land uses of the catchments, both as they were in 1992 and as they are today. These flood discharges were then used in a 2D shallow water model to estimate the increase of water depths in the city from 1992 to the present day. To evaluate the influence of urban expansion on inundation levels, three future urbanization scenarios were proposed on the basis of the urban growth rate forecast for 2050. Results confirm that the change in land use in the hydrological catchments is the main factor that explains the increase in inundation events observed over recent years. This study also provides useful insights for future city planning that might help to minimize the flood impact on Villahermosa.
Research on Mushroom Image Classification Algorithm Based on Deep Sparse Dictionary Learning

The traditional mushroom feature extraction method has low classification efficiency and unsatisfactory effect. Dictionary learning is widely used in image classification. However, the previous work is to learn dictionaries in the original space, which limits the performance of sparse representation classification. In order to solve the problem of spatial redundancy in traditional convolutional neural networks and the weak performance of deep learning in small samples, an improved dictionary learning algorithm, Deep Sparse Dictionary learning (DSDL), is proposed. The input to DSDL is not a matrix gathered from the original grayscale image or a hand-created feature, but rather a relatively deeper feature extraction via a stack autoencoder. Then, a structured dictionary is designed to reconstruct the deep features according to different categories of distinguishing features. In addition, it is necessary to learn the associated structured projection sparse dictionary to ensure that the decoder updates in the direction of the deconvolution operator error is minimal. By utilizing sparse dictionary learning loss functions and autoencoder loss functions, DSDL can simultaneously learn deep latent features and corresponding dictionary pairs. In the testing phase of DSDL, the minimum errors of deep feature and structured projection components for different classes can be directly represented by basic matrix multiplication operations. Experimental results show that the proposed method achieves a good classification effect on mushroom images, which shows the effectiveness of the method.
Cytogenotoxic effect of trichothecene T2 toxin on Allium sativum root tip meristematic cells

Trichothecene T2 is a mycotoxin from the Fusarium species. This research aims to test the effect of the Trichothecene T2 toxin on mitotic index% (M.I.%) and induction of mitotic aberrations by using the Allium sativum (garlic) test system. The toxin concentrations in ppm were 0.00, 0.30, 0.60, 0.90, and 1.20 for 12 hours. The garlic roots were then cut, and mitotic slides were prepared using squash and examined under a light microscope. The results revealed that the mycotoxin has a significant mitodepressive effect at all concentrations compared to the control, and the MI% reduction was proportional to increasing toxin concentration. The highest reduction in mitotic index was observed in the 1.2 ppm treatment. Moreover, this mycotoxin induced and increased the rate of mitotic abnormalities% (MA%) with increasing the mycotoxin concentration. The observed mitotic abnormalities were star-shaped anaphase, sticky metaphase, C-mitosis, sticky anaphase, depolarization, micronuclei, laggard chromosomes, anaphase bridges, and chromosome loss. The least frequently observed abnormality was micronuclei compared to the most frequent aberration, laggard chromosomes. The total mitotic abnormalities significantly increased with increasing the toxin dose concentration. These results suggest that this mycotoxin can inhibit the mitotic activity of the meristematic cells; it is mutagenic and can disrupt the spindle fibers' activity of the dividing cells at all concentrations, especially at higher doses in food. Therefore, the foods must be tested for fungi producing this mycotoxin. Keywords: Mycotoxin; mitodepressive; root tip; spindle fibers; mutagenic
Maternal vgll4a regulates zebrafish epiboly through Yap1 activity

Gastrulation in zebrafish embryos commences with the morphogenetic rearrangement of blastodermal cells, which undergo a coordinated spreading from the animal pole to wrap around the egg at the vegetal pole. This rearrangement, known as epiboly, relies on the orchestrated activity of maternal transcripts present in the egg, compensating for the gradual activation of the zygotic genome. Epiboly involves the mechano-transducer activity of yap1 but what are the regulators of yap1 activity and whether these are maternally or zygotically derived remain elusive. Our study reveals the crucial role of maternal vgll4a, a proposed Yap1 competitor, during zebrafish epiboly. In embryos lacking maternal/zygotic vgll4a (MZvgll4a), the progression of epiboly and blastopore closure is delayed. This delay is associated with the ruffled appearance of the sliding epithelial cells, decreased expression of yap1-downstream targets and transient impairment of the actomyosin ring at the syncytial layer. Our study also shows that, rather than competing with yap1, vgll4a modulates the levels of the E-cadherin/β-catenin adhesion complex at the blastomeres’ plasma membrane and hence their actin cortex distribution. Taking these results together, we propose that maternal vgll4a acts at epiboly initiation upstream of yap1 and the E-cadherin/β-catenin adhesion complex, contributing to a proper balance between tissue tension/cohesion and contractility, thereby promoting a timely epiboly progression.
Testing of Portfolio Optimization by Timor-Leste Portfolio Investment Strategy on the Stock Market

An efficient and effective portfolio provides maximum return potential with minimum risk by choosing an optimal balance among assets. Therefore, the objective of this study is to analyze the performance of optimized portfolios in minimizing risk and achieving maximum returns in the dynamics of Timor-Leste’s equity portfolio in the international capital market for the period from January 2006 to December 2019. The empirical findings of this study indicate that the correlation matrix showed that JPM has a very strong positive correlation with one of the twenty assets, namely BAC (0.80). Moreover, the optimal portfolio of the twenty stocks exceeding 10% consists of four consecutive stocks, namely DGE.L (10.69%), NSRGY (10.37%), JPM (10.04%), and T (10.03%). In addition, the minimum portfolio consists of two stocks with a minimum variance of more than 10%, namely SAP.DE (11.20%) and DGE.L (10.39%). The evaluation of the optimal portfolio using Markowitz parameters also showed that the highest expected return and the lowest risk were 1.22% and 3.12%, respectively.