Splitting Procedure Research Articles

The Correlational Study of Percentage of Heamoglobin in Patients who are Undergoing Split Skin Graft Procedure

The Correlational Study of Percentage of Heamoglobin in Patients who are Undergoing Split Skin Graft Procedure

A study on generalized balanced split drift stochastic Runge- Kutta methods for stochastic differential equations

To reduce computational complexity, the balanced numerical approximations of the general split drift stochastic Runge-Kutta methods are analyzed. The primary reasons for considering the numerical approximations of these balanced split stochastic Runge-Kutta methods are their improved stability characteristics and lower mean square error compared to other methods. By balancing the drift and diffusion components, the splitting techniques outperform the mean square error over longer time increments. For Ito multi-dimensional stochastic differential equations, we propose a novel family of balanced universal split stochastic Runge-Kutta procedures. The Kronecker product concept is utilized to derive the mean-square stability conditions. We conduct numerical tests to evaluate these methods against an existing weak order 2 split drift method. Ultimately, a specific numerical example validates the theoretical outcomes of the balanced general split stochastic Runge-Kutta procedures.

Glottic widening procedures (GWPs) to avoid tracheostomy in infants’ bilateral vocal cord paralysis: A systematic review and meta-analysis

ObjectiveThis systematic review and meta-analysis evaluated the efficacy of various glottic widening procedures (GWPs) in avoiding tracheostomy in infants with bilateral vocal cord paralysis (BVCP). MethodsA systematic literature search was conducted in PubMed, Scopus, Web of Science, and Cochrane Library from inception to July 2023, without any timeframe limitations. Studies reporting GWPs (Endoscopic anterior-posterior cricoid split, Botox injection, suture lateralization, and other procedures including laser posterior cordotomy/arytenoidectomy) in infants with BVCP were included. Meta-analysis was performed to assess tracheostomy avoidance and secondary outcomes including voice, swallowing, and resolution of airway symptoms. ResultsThirteen studies with 100 patients were included. The mean age was 51.6 days. The etiology of BVCP was idiopathic (83 %), neurologic (10 %), and acquired (7 %). The GWP interventions were successful in 88 % of patients, with only 12 % requiring tracheostomy after surgery. The pooled proportion for avoiding tracheostomy was 0.88 (95 % CI 0.82–0.94) across interventions, with no significant differences between techniques. Among patients who avoided tracheostomy, 64 % had normal voice, 86 % tolerated oral feeding, 77 % had airway symptom resolution, and 70 % had recovery of vocal cord mobility. ConclusionGWPs prevent a majority of infants with BVCP from undergoing tracheostomy, without permanent alterations to laryngeal function. All interventions were comparable in efficacy. Further research with larger sample sizes is warranted.

Does the modified inferior border osteotomy improve the surgical outcomes in bilateral sagittal split osteotomy?

BackgroundTo investigate the effect of lower border osteotomy on the lingual split pattern and IAN in BSSO procedures. Materials and MethodsThe study comprised 32 patients (64 operated sides) who underwent bilateral sagittal split osteotomy (BSSO) due to dentofacial abnormalities between the periods of April 2021 and April 2022. In the mandible, 32 sides (the conventional group) received standard BSSO surgery, while 32 sides (the modified group) additionally received lower border osteotomy. Data regarding the split difficulty of the mandibular in BSSO surgery and the recovery status of the inferior alveolar nerve (IAN) one year after surgery were obtained and evaluated from patient records. The fracture line was radiographically evaluated for the lingual split pattern following surgery. ResultsA statistically significant difference was observed in favor of the modified group when the mandibular split difficulty of the groups was compared (p=0.032). The split time of the modified group was found to be statistically shorter than the conventional group (p≤0.001). The mean numbness level of the modified group one year after surgery was statistically significantly lower than that of the conventional group (p = 0.019). Although there was no statistically significant difference between the two groups in terms of lingual fracture pattern, the rate of type 1 (87.5%) fracture was higher in the modified group compared to the other group (68.8%) (p=0.089). ConclusionThe lower border osteotomy performed in addition to the conventional BSSO surgery allows the split procedure easier and in a shorter time. The modification resulted in an increased incidence of type 1 lingual fracture pattern in the mandible. The neurosensory recovery capacity of the IAN in the postoperative period is higher in areas where lower-border osteotomies are performed.

Model-Based Prediction for Small Domains Using Covariates: A Comparison of Four Methods

Abstract We consider methods for model-based small area estimation when the number of areas with sampled data is a small fraction of the total areas for which estimates are required. Abundant auxiliary information is available from the survey for all the sampled areas. Further, through an external source, there is information for all areas. The goal is to use auxiliary variables to predict the outcome of interest for all areas. We compare areal-level random forests and LASSO approaches to a frequentist forward variable selection approach and a Bayesian shrinkage method using a horseshoe prior. Further, to measure the uncertainty of estimates obtained from random forests and the LASSO, we propose a modification of the split conformal procedure that relaxes the assumption of exchangeable data. We show that the proposed method yields intervals with the correct coverage rate and this is confirmed through a simulation study. This work is motivated by Ghanaian data available from the sixth Ghana Living Standards Survey (GLSS) and the 2010 Population and Housing Census, in the Greater Accra Metropolitan Area (GAMA) region, which comprises eight districts that are further divided into enumeration areas (EAs). We estimate the areal mean household log consumption using both datasets. The outcome variable is measured only in the GLSS for 3 percent of all the EAs (136 out of 5019) and 174 potential covariates are available in both datasets. In the application, among the four modeling methods considered, the Bayesian shrinkage performed the best in terms of bias, mean squared error (MSE), and prediction interval coverages and scores, as assessed through a cross-validation study. We find substantial between-area variation with the estimated log consumption showing a 1.3-fold variation across the GAMA region. The western areas are the poorest while the Accra Metropolitan Area district has the richest areas.

ZnAl2O4 decorated on graphitic carbon nitride (g-CN) composite as efficient electrocatalyst for water oxidation in alkaline medium

The main purpose of this research is to form highly effective and novel electrocatalysts for water splitting procedure, a pivotal step in the generation of sustainable energy. Cost-effective metal oxides exhibited superior benefits compared to alternative materials when used for oxygen evolution reactions (OER) in alkaline electrolyte. Our study focuses on the preparation of ZnAl2O4@g-CN composite by utilizing hydrothermal approach for electrocatalytic water splitting. The electrocatalytic potential of prepared electrocatalyst was observed by a comprehensive series of tests. Numerous electrochemical approaches such as chronoamperometry and electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV) were implemented to analyze catalytic procedure and durability in basic medium. The electrocatalytic tests of ZnAl2O4@g-CN composite reveal a remarkable overpotential of 209 mV, enabling the attainment of current density (Cd) 10 mA/cm2. Additionally, the composite shows significantly lower Tafel value (36 mV/dec) and has remarkable durability for 30 h. These characteristics mutually designate that electrocatalyst is well-suited for OER procedure. Therefore, the fabricated composite exhibited excellent efficacy in OER procedure as well as for several other upcoming applications.

Concomitant Extraction of Wisdom Teeth with Bilateral Sagittal Split Osteotomy (BSSO): A Case Series

Aim: Aim:To investigate the incidence of postoperative complications (including pain, nerve damage, swelling and infection) associated with the concomit an textraction of wisdom teeth at the time of bilateral sagittal split osteotomy procedures. Materials and Methods: A retrospective evaluation of eight patients who underwent concomitant removal of their lower wisdom teeth (either fully erupted, partially or fully bone impacted) at the time of their surgical procedure (Bilateral sagittal split osteotomy with/without LeFort 1 procedure/genioplasty). All patients presented to the Oral and Maxillofacial Surgery Department at Case Western Reserve University. Postoperative complications (including pain, nerve dysfunction, swelling and infection) were examined at regular follow-up appointments after their surgical procedure. Results: A total of eight patients were examined for post operative complications. All patients confirmed the presence of mild pain/discomfort/swelling in the short-term postoperatively.

Outcomes of Donor Corneas of Different Thicknesses From Endothelial Keratoplasty in Deep Anterior Lamellar Keratoplasty for Keratoconus.

To evaluate the outcomes of divided residual donor corneas obtained from endothelial keratoplasty in keratoconus with deep anterior lamellar keratoplasty (DALK). In this retrospective, comparative, clinical study, 103 keratoconic eyes that underwent DALK were enrolled; 67 eyes received thin grafts from Descemet stripping automated endothelial keratoplasty, and 36 received thick grafts from Descemet membrane endothelial keratoplasty. Baseline and postoperative central corneal thickness (CCT), inferior corneal thickness, uncorrected distance visual acuity, corrected distance visual acuity, corneal astigmatism, mean keratometry, biomechanical properties, and complication rates were measured. Six months after transplantation, the group receiving thin grafts had a CCT of only 455.1 ± 43.0 μm, whereas that of the group receiving thick grafts was 546.7 ± 44.2 μm. Both CCT and inferior corneal thickness in the thin group were significantly lower than those in the thick group (measured with Pentacam at 36 months, P < 0.001) and remained throughout the 5-year follow-up period. Both procedures had comparable postoperative logarithm of the minimum angle of resolution UDVAs, logarithm of the minimum angle of resolution corrected distance visual acuity, astigmatism, and mean keratometry values (36 months; P = 0.335, 0.286, 0.680, and 0.365, respectively). Corneal biomechanical analysis revealed that the thin group had a significantly higher stiffness parameter at the first applanation than the thick group at the 2-year follow-up (P = 0.036) while other parameters were equivalent. The outcomes of keratoplasty with donor tissue are comparable regardless of the thickness of the graft, which suggests that transplantation with either type of the split corneal procedure for DALK in patients with keratoconus is feasible.

Controlling numerical diffusion in solving advection-dominated transport problems

Numerical schemes for advection-dominated transport problems are are evaluated in a comparative study. Explicit and implicit finite difference methods are analyzed together with a global random walk algorithm in the frame of a splitting procedure. The efficiency of the methods with respect to the control of the numerical diffusion is investigated numerically on one-dimensional problems with constant coefficients and two-dimensional problems with variable coefficients consisting of realizations of space-random functions.

Adaptive parameters tuning based on energy-preserving splitting integration for Hamiltonian Monte Carlo Method

Splitting schemes, a class of numerical integrators for Hamiltonian problems, offer a favorable alternative to the Störmer–Verlet method in Hamiltonian Monte Carlo (HMC) methodology. However, the performance of HMC is highly sensitive to the adopted step size. In this paper, we propose a novel approach for selecting the step size h for advancing with the method defined by the free parameter b, within the family of one-parameter second order splitting procedures. Our methodology utilizes a designated function hb of the parameter b to determine the step size, i.e. h=hb(b). By appropriately restricting the domain of hb to a suitable interval I, the pairs (b,hb) with b∈I ensure both stability and Hamiltonian preservation when sampling from Gaussian distributions. As a result, our technique never rejects a sample within the HMC process, and this characteristic is the key factor behind its superior performance compared to similar methods recently introduced in other studies. Additionally, we assess the effectiveness of the methods defined by the pairs (b,hb) for general not-Gaussian distribution sampling. In this case we also present a technique based on an adaptive selection of the b parameter for improving the HMC performance. The effectiveness of the proposed approach is evaluated through benchmark examples from literature and experiments involving the Log-Gaussian Cox process and Bayesian Logistic Regression.

Optimal transport for automatic alignment of untargeted metabolomic data.

Untargeted metabolomic profiling through liquid chromatography-mass spectrometry (LC-MS) measures a vast array of metabolites within biospecimens, advancing drug development, disease diagnosis, and risk prediction. However, the low throughput of LC-MS poses a major challenge for biomarker discovery, annotation, and experimental comparison, necessitating the merging of multiple datasets. Current data pooling methods encounter practical limitations due to their vulnerability to data variations and hyperparameter dependence. Here, we introduce GromovMatcher, a flexible and user-friendly algorithm that automatically combines LC-MS datasets using optimal transport. By capitalizing on feature intensity correlation structures, GromovMatcher delivers superior alignment accuracy and robustness compared to existing approaches. This algorithm scales to thousands of features requiring minimal hyperparameter tuning. Manually curated datasets for validating alignment algorithms are limited in the field of untargeted metabolomics, and hence we develop a dataset split procedure to generate pairs of validation datasets to test the alignments produced by GromovMatcher and other methods. Applying our method to experimental patient studies of liver and pancreatic cancer, we discover shared metabolic features related to patient alcohol intake, demonstrating how GromovMatcher facilitates the search for biomarkers associated with lifestyle risk factors linked to several cancer types.

Optimal transport for automatic alignment of untargeted metabolomic data

Untargeted metabolomic profiling through liquid chromatography-mass spectrometry (LC-MS) measures a vast array of metabolites within biospecimens, advancing drug development, disease diagnosis, and risk prediction. However, the low throughput of LC-MS poses a major challenge for biomarker discovery, annotation, and experimental comparison, necessitating the merging of multiple datasets. Current data pooling methods encounter practical limitations due to their vulnerability to data variations and hyperparameter dependence. Here, we introduce GromovMatcher, a flexible and user-friendly algorithm that automatically combines LC-MS datasets using optimal transport. By capitalizing on feature intensity correlation structures, GromovMatcher delivers superior alignment accuracy and robustness compared to existing approaches. This algorithm scales to thousands of features requiring minimal hyperparameter tuning. Manually curated datasets for validating alignment algorithms are limited in the field of untargeted metabolomics, and hence we develop a dataset split procedure to generate pairs of validation datasets to test the alignments produced by GromovMatcher and other methods. Applying our method to experimental patient studies of liver and pancreatic cancer, we discover shared metabolic features related to patient alcohol intake, demonstrating how GromovMatcher facilitates the search for biomarkers associated with lifestyle risk factors linked to several cancer types.

Combined physical and biogeochemical assessment of mesoscale eddy parameterisations in ocean models: Eddy-induced advection at eddy-permitting resolutions

Ocean general circulation models at the eddy-permitting regime are known to under-resolve the mesoscale eddy activity and associated eddy-mean interaction. Under-resolving the mesoscale eddy field has consequences for the resulting mean state, affecting the modelled ocean circulation and biogeochemical responses, and impacting the quality of climate projections. There is an ongoing debate on whether and how a parameterisation should be utilised in the eddy-permitting regime. Focusing on the Gent–McWilliams (GM) based parameterisations, it is known that, on the one hand, not utilising a parameterisation leads to insufficient eddy feedback and results in biases. On the other hand, utilising a parameterisation leads to double-counting of the eddy feedback, and introduces other biases. A recently proposed approach, known as splitting, modifies the way GM-based schemes are applied in eddy-permitting regimes, and has been demonstrated to be effective in an idealised Southern Ocean channel model. In this work, we evaluate whether the splitting approach can lead to improvements in the physical and biogeochemical responses in an idealised double gyre model. Compared with a high resolution mesoscale eddy resolving model truth, the use of the GM-based GEOMETRIC parameterisation together with splitting in the eddy-permitting regime leads to broad improvements in the control pre-industrial scenario and an idealised climate change scenario, over models with and models without the GM-based GEOMETRIC parameterisation active. While there are still some deficiencies, particularly in the subtropical region where the transport is too weak and may need momentum re-injection to reduce the biases, the present work provides further evidence in support of using the splitting procedure together with a GM-based parameterisation in ocean general circulation models at eddy-permitting resolutions.

Public views about the world's largest proposed solar farm in remote Australia

The world's largest solar farm is planned for a remote part of northern Australia. Construction of the 12,000 ha of solar arrays will create local jobs but may have substantial environmental and social impacts. Despite its unprecedented size, little is known about societal views of the farm, potentially undermining its public acceptance. Using a split sampling procedure, we surveyed emotions and other views of the solar farm among residents of the same jurisdiction, some of whom may benefit economically (n = 124), and the broader public across the rest of Australia (n = 2099). Most people (70%) felt positive about the farm with 24% feeling proud and 46% of respondents expressing hope. Those living relatively close to the proposed solar farm held the strongest positive views. The strong support and high levels of trust in the developer contrasts strongly with the often vehement opposition to wind farms. Nevertheless, approximately a third of respondents were concerned that, although remote, the solar farm could detract from the region's environment as being inappropriate for the remote landscape, with Indigenous respondents being particularly cautious. The results can be used for community consultations and contribute to understanding of the public acceptance of solar farms, which has to date been dominated by research on wind energy projects.

Alveolar Ridge Split and Expansion Utilising a Piezo-surgical Approach for Implant Placement in Narrow Ridges

Abstract In clinical settings, it is common to encounter alveolar ridges that lack sufficient width, posing challenges for implant placement. To ensure a successful implant placement, the bone’s width must be at least 1.5 mm greater than the implant’s diameter on both the buccal and lingual/palatal sides. The alveolar ridge split technique has been developed as a solution for horizontal bone deficiencies, allowing for the expansion of the alveolar ridges. This article discusses a case where an implant was placed in a 35-year-old male patient who had a missing lower left first molar for 5 years. Due to the horizontal deficiency of the alveolar ridge, a ridge split and expansion procedure was executed using piezosurgery. After 6 months, a screw-retained prosthesis was successfully delivered.

Self‐Supported Electrocatalyst for Seawater Splitting

AbstractOver the past decades, tremendous effort has been made to enhance the water‐splitting via fabricating eco‐friendly electrocatalyst with increased conductivity, and large number of accessible active sites in lab scale. However, the development of earth abundant efficient electrocatalyst with superior activity for ‐seawater‐splitting remains a great challenge for the researchers. In this regard, self‐supported catalysts are found to be the most promising candidates, they have the features of increased loading, superior adhesion, rapid mass and charge transfer, and easy wettability for large scale hydrogen production via electrochemical seawater splitting. This review investigates different fabrication processes for the self‐supported catalyst, emphasizing their distinct characteristics that contribute to improved activity. Furthermore, we provided a detailed elucidation of the procedure and characteristics of seawater splitting, emphasizing the most recent progress in the creation of self‐supportive catalyst for the hydrogen evolution reaction (HER), oxygen evolution reaction (OER), and bifunctional activity. We have also examined the current barriers and potential prospects for advancing the utilization of self‐supported catalysts in the process of seawater splitting.

Efficiency of machine perfusion in pediatric liver transplantation.

Liver transplantation is the only life-saving procedure for children with end-stage liver disease. The field is however heterogenic with various graft types, recipient age, weight, and underlying diseases. Despite recently improved overall outcomes and the expanded use of living donors, waiting list mortality remains unacceptable, particularly in small children and infants. Based on the known negative effects of elevated donor age, higher body mass index, and prolonged cold ischemia time, the number of available donors for pediatric recipients is limited. Machine perfusion has regained significant interest in the adult liver transplant population during the last decade. Ten randomized controlled trials are published with an overall advantage of machine perfusion techniques over cold storage regarding postoperative outcomes, including graft survival. The concept of hypothermic oxygenated perfusion (HOPE) was the first and only perfusion technique used for pediatric liver transplantation today. In 2018 the first pediatric candidate received a full-size graft donated after circulatory death with cold storage and HOPE, followed by a few split liver transplants after HOPE with an overall limited case number until today. One series of split procedures during HOPE was recently presented by colleagues from France with excellent results, reduced complications, and better graft survival. Such early experience paves the way for more systematic use of machine perfusion techniques for different graft types for pediatric recipients. Clinical reports of pediatric liver transplants with other perfusion techniques are awaited. Strong collaborative efforts are needed to explore the effect of perfusion techniques in this vulnerable population impacting not only the immediate posttransplant outcome but the development and success of an entire life.

A Bidirectional Arabic Sign Language Framework Using Deep Learning and Fuzzy Matching Score

Sign language is widely used to facilitate the communication process between deaf people and their surrounding environment. Sign language, like most other languages, is considered a complex language which cannot be mastered easily. Thus, technology can be used as an assistive tool to solve the difficulties and challenges that deaf people face during interactions with society. In this study, an automatic bidirectional translation framework for Arabic Sign Language (ArSL) is designed to assist both deaf and ordinary people to communicate and express themselves easily. Two main modules were intended to translate Arabic sign images into text by utilizing different transfer learning models and to translate the input text into Arabic sign images. A prototype was implemented based on the proposed framework by using several pre-trained convolutional neural network (CNN)-based deep learning models, including the DenseNet121, ResNet152, MobileNetV2, Xception, InceptionV3, NASNetLarge, VGG19, and VGG16 models. A fuzzy string matching score method, as a novel concept, was employed to translate the input text from ordinary people into appropriate sign language images. The dataset was constructed with specific criteria to obtain 7030 images for 14 classes captured from both deaf and ordinary people locally. The prototype was developed to conduct the experiments on the collected ArSL dataset using the utilized CNN deep learning models. The experimental results were evaluated using standard measurement metrics such as accuracy, precision, recall, and F1-score. The performance and efficiency of the ArSL prototype were assessed using a test set of an 80:20 splitting procedure, obtaining accuracy results from the highest to the lowest rates with average classification time in seconds for each utilized model, including (VGG16, 98.65%, 72.5), (MobileNetV2, 98.51%, 100.19), (VGG19, 98.22%, 77.16), (DenseNet121, 98.15%, 80.44), (Xception, 96.44%, 72.54), (NASNetLarge, 96.23%, 84.96), (InceptionV3, 94.31%, 76.98), and (ResNet152, 47.23%, 98.51). The fuzzy matching score is mathematically validated by computing the distance between the input and associative dictionary words. The study results showed the prototype’s ability to successfully translate Arabic sign images into Arabic text and vice versa, with the highest accuracy. This study proves the ability to develop a robust and efficient real-time bidirectional ArSL translation system using deep learning models and the fuzzy string matching score method.

Cell-centered indirect Arbitrary Lagrangian-Eulerian numerical strategy for solving 3D gas dynamics equations

Solving the Euler equations under the Lagrangian formalism enables to simulate various complex engineering applications. However, the use of this formalism can lead to significant mesh deformations as the mesh follows the fluid velocity. The mesh quality may be considerably deteriorated requiring a regularization procedure. In the present document, it is shown that the ideas presented by J. Yao (2013)[68] and J. Yao and D. Stillman (2016) [30] may be used efficiently in a 3D hydrodynamics code to perform reliable regularization steps. The flexibility of the methodology in addition to its simplicity, since it only relies on trivial geometrical considerations, opens the way for various extensions. The remapping step then considered, uses the geometrical splitting procedure of the Lagrangian phase to perform effective projections. This coherence ensures the compactness of the overall algorithm. At last but not least, a 3D Flux-Corrected-Remapping method is presented. This yields a particularly robust remapping algorithm while also leading the way for higher order projection extensions.

Towards targeted Cas9 (CRISPR-Cas) delivery: Preparation of IgG antibody-Cas9 conjugates using a split intein.

The CRISPR-Cas9 system has revolutionized the field of genetic engineering, but targeted cellular delivery remains a central problem. The delivery of the preformed ribonuclease-protein (RNP) complex has the advantages of fewer side effects and avoidance of potential permanent effects. We reasoned that an internalizing IgG antibody as a targeting device could address the delivery of Cas9-RNP. We opted for protein trans-splicing mediated by a split intein to facilitate posttranslational conjugation of the two large protein entities. We recently described the cysteine-less CL split intein that efficiently performs under oxidizing conditions and does not interfere with disulfide bonds or thiol bioconjugation chemistries. Using the CL split intein, we report for the first time the ligation of monoclonal IgG antibody precursors, expressed in mammalian cells, and a Cas9 precursor, obtained from bacterial expression. A purified IgG-Cas9 conjugate was loaded with sgRNA to form the active RNP complex and introduced a double-strand break in its target DNA in vitro. Furthermore, a synthetic peptide variant of the short N-terminal split intein precursor proved useful for chemical modification of Cas9. The split intein ligation procedure reported here for IgG-Cas9 provides the first step towards a novel CRISPR-Cas9 targeting approach involving the preformed RNP complex.