Multilayer Technique Research Articles

Cutaneous Layer and SMAS Suspension (CaSS) Lift as a Minimally Invasive Lateral Midface Lift.

In our prior study, the authors determined that pulling on the superficial adipose layer is more effective in lifting the skin than pulling on the superficial musculoaponeurotic system (SMAS). Applying this concept of using the superficial adipose layer to transmit the lifting force to the skin, this study examined improvements in patients who underwent lateral midface lifting using our minimally invasive multilayer lifting technique and measured the duration of those improvements. Along the hairline in front of the sideburns, a W-shaped zigzag incision of 3 to 8mm in width and 3 to 4cm in length was made. On the temporal scalp, 3 to 4cm away from the first incision, a second incision was made more lateral/posterior to the first incision, and an elliptical excision of 3 to 5mm in width and 3 to 4cm in length was made. From the medial cut margin of the anterior first incision, the superficial temporal fascia/SMAS (the deep layer), and the superficial adipose layer (the superficial layer) were purchased with 3-0 polyester sutures, tunneled under the soft tissue, and fixed to the deep temporal fascia of the second posterior temporal incision. Prior to the excised temporal scalp closure, the dermis in the medial cut margin of the second incision was pulled to the rear as much as possible and fixed to the deep temporal fascia. The effects of surgery were monitored for 6 to 42 months after surgery. The nasolabial folds were improved. Skin elasticity also showed significant improvements, which lasted throughout the follow-up period (up to 42mo). Unlike traditional wide dissection SMAS facelift, our method requires minimal incisions and does not require skin undermining. Therefore, the operating time is shorter, and postoperative swelling is minimized. In our technique, the superficial adipose layer, the superficial temporal fascia/SMAS, and the dermis were pulled individually to lift all layers of the lateral midface soft tissues. This results in a significant and long-lasting lateral midface rejuvenation.

Cyber Threat Detection Based on Artificial Neural Networks

Abstract: Finding an automated method for detecting cyber-attacks is one of the biggest problems in cybersecurity. We describe an artificial intelligence (AI) method based on deep learning for detecting cyber threats. The suggested solution uses a deep attempting to learn monitoring method to improve cyber-threat identification by breaking down a large volume of recorded security events into event profiles. We created an AI-SIEM system that combines event profiles for data pretreatment with several multilayer perceptron techniques, such as FCNN, CNN, and LSTM. The approach focuses on separating real positive warnings from misdiagnosis alerts to assist experts in quickly responding to cyber-attacks. We carried out tests utilising the five traditional machine-learning techniques to assess the comparison study with existing approaches (SVM, k-NN, RF, NB, and DT). The experimental findings of this study confirm that our suggested methods may be used as studying models for activity recognition and demonstrate that, when used in the real life, they outperform traditional auto techniques.

Evaluation of the global solar irradiation from the artificial neural network technique

In this study, many experiments were carried out to assess the influence of the some input parameters on performance of the multilayer perceptron techniques, which is architectures one of the artificial neural network (ANN). To estimate the daily global solar irradiation (GSI) on horizontal surface, we have developed eight models by using four weather input parameters collected from a radiometric station installed at Ghardaia site (southern of Algeria), such as sunshine duration, daily mean temperature, daily relative humidity, and Solar declination. In order to select the best configuration among the chooses combinations which provides a good accuracy, three statistical formulas (or statistical indicators) have been evaluated, such as the normalized root mean square errors, (nRMSE), normalized mean bias error (nMBE, and coefficient of determination R²). We noted that the ANN model provides best performance compared to the developed empirical models. results of the nMBE, nRMSE, and R² are about 0.048%, 4.422%, and 98.00%, for ANN and 0.0772%, 5.5381%, and 97.22% for the quadratic model. Moreover, it was proved that the sunshine duration is important parameter, for predicting the GSI.

Disk Failure Prediction based on Multi-layer Domain Adaptive Learning

Large scale data storage is susceptible to failure. As disks are damaged and replaced, traditional machine learning models, which rely on historical data to make predictions, struggle to accurately predict disk failures. This paper presents a novel method for predicting disk failures by leveraging multi-layer domain adaptive learning techniques. First, disk data with numerous faults is selected as the source domain, and disk data with fewer faults is selected as the target domain. A training of the feature extraction network is performed with the selected origin and destination domains. The contrast between the two domains facilitates the transfer of diagnostic knowledge from the domain of source and target. According to the experimental findings, it has been demonstrated that the proposed technique can generate a reliable prediction model and improve the ability to predict failures on disk data with few failure samples.

Multiple-layer statistical methodology for developing data-driven models of anaerobic digestion process

When modelling anaerobic digestion, ineffective data handling and inadequate designation of modelling parameters can undermine the model reliability. In this study, a multilayer statistical technique, which employed a machine learning technique using regression models, was introduced to systematically support the development of anaerobic digestion models. Layer-by-layer statistical techniques including cubic smoothing splines (missing data reconstruction), principal component analysis (identifying correlated parameters), analysis of variance (analysing differences among datasets), and linear regression (developing data-driven models) were used to develop and validate anaerobic digestion models. Experimental data collected from the long-term operation of lab-scale (operated for 350 days), pilot-scale (operated for 150 days), and full-scale reactors (operated for 750 days) were used to demonstrate the modelling process. The multivariate models based on a data-driven modelling technique were developed by subjecting the experimental and monitored data to a modelling process. The developed models could predict the biogas production and effluent chemical oxygen demand during anaerobic digestion. Statistical analyses verified the modelling hypotheses, evaded invalid model development, and ensured data integrity and parameter validity. Multiple linear regression of principal components demonstrated that the performance of biogas production using food waste was influenced by the variances of the nitrogen and organic concentrations, but not by the chemical oxygen demand to total nitrogen (C/N) ratio. In the validation process, the model developed with lab-scale reactor data showed relatively high accuracy with R2, SSE, and RMSE values of 0.86, 34.45, and 0.72.

Marginal Adaptation of In Vitro Class II Restorations Made Out of Bulk or Conventional Composite Using Single- or Multi-Layered Techniques.

Objective: Testing the influence of various restorative materials (conventional or bulkfill composites) and filling techniques (single- or multi-layered techniques) on the in vitro marginal adaptation of large class II direct composites with supra and sub-gingival margins subjected to thermomechanical loading (TML). Methods: A total of 40 prepared teeth were attributed randomly to five experimental groups. In Group 1, restorations were made of multi-layered high-viscosity conventional composite (Tetric EvoCeram); in Groups 2 and 3, restorations were made of a high viscosity bulkfill composite (Tetric EvoCeram Bulk Fill) applied in one (Group 2) or three layers (Group 3); in Groups 4 and 5, restorations were made of a flowable bulkfill composite (SDR flow) applied in one (Group 4) or two layers (Group 5), covered with a layer of high-viscosity conventional composite (Ceram-X Universal). A single adhesive (OptiBond FL) was used in all groups. All specimens were submitted to a staged TML comprising three phases (2 × 500,000 and 1,000,000 cycles) at 50 N with 3350 thermal cycles (5 to 55 °C) every 500,000 cycles. The tooth-restoration interfaces on proximal surfaces were evaluated quantitatively by scanning electron microscopy, before and after each TML phase, hence at three timepoints (T0, T1, T2 and T3). The following segments were considered for evaluation: proximal, vertical enamel margins (assessed individually on both restoration sides), cervical enamel (restoration side above CEJ) and cervical dentin margin (restoration side below the CEJ). Results: TML induced a significant reduction in continuous adaptation at both enamel and dentin margins in all groups, with percentages of continuous margins ranging from 75.2 to 91.8% at T0, and decreasing to values ranging from 21.3 to 73.9% at T3. Both composite systems and layering protocols had a significant influence on marginal adaptation of the restorations, with statistical associations depending on the restoration group and the timepoint considered. Defective margins in enamel were all of a cohesive nature with micro-fractures, while in dentin, interfacial gaps were the main defect observed. Conclusions/Clinical significance: The present results highlighted significant degradation of marginal adaption after long-term in vitro fatigue test using materials even with high-viscosity conventional resin composites, applied with a proper layering approach in medium-large sub-gingival cavities. While no significant differences were observed at the dentin cervical margins, there was a tendency for better adaptation at the enamel margin when using a higher modulus material with a multi-layered technique.

Efficacy of hydroxyapatite-based skull base reconstruction for intraoperative high-flow cerebrospinal fluid leakage performed by less-experienced surgeons

Cerebrospinal fluid (CSF) leakage after endoscopic skull base surgery remains a challenge despite multilayer reconstruction including nasoseptal flap (NSF) has become a standard technique. Injectable hydroxyapatite (HXA) has shown promising results to prevent CSF leakage. This study aimed to validate the efficacy of HXA-based skull base reconstruction performed by less-experienced neurosurgeons who had short-term clinical experiences as independent surgeons. Between March 2018 and November 2022, 41 patients who experienced intraoperative high-flow CSF leakage following endoscopic endonasal surgery at two independent tertiary institutions were enrolled. Skull base reconstruction was performed using conventional multilayer techniques combined with or without HXA. The primary outcome was postoperative CSF leakage. The surgical steps and nuances were described in detail. The most common pathology was craniopharyngioma. Injectable HXA was used in 22 patients (HXA group) and conventional techniques were performed in 19 patients (control group). The HXA group achieved a significantly lower incidence of postoperative CSF leakage than the control group (0% vs. 26.3%, p = 0.016). No HXA-related complications were observed. The use of injectable HXA in skull base reconstruction was highly effective and safe. This technique and its favorable results might be readily reproduced by less-experienced neurosurgeons.

Spam email detection using a novel multilayer classification-based decision technique

Because of the rapid advancement of technology over the last several years, the number of internet users is growing at an exponential rate, and as a result, email communication has become popular as a means of exchanging information over the internet. Sending data and communicating with peers via email is the most cost-effective method. These email services also cause problems for users by sending electronic junk mail, often known as spam mail. Spam email is a privacy concern that is linked to a slew of commercial and dangerous websites, causing phishing, virus distribution, and a slew of other problems. This study examines several aspects that have been used for email spam classification, as well as offering an overview of a handful of classifiers or algorithms that have been successfully evaluated, as well as exploratory data analysis. The proposed email spam classifier uses three parallel layers of machine learning and deep learning techniques, followed by a decision function to determine whether or not the emails are spam. During testing, it was found that the proposed classifier beats similar systems on the standard dataset with an accuracy of 98.4%.

0‐3 magnetic nanocomposites via EPD: Current status for power component fabrication and future directions

AbstractInductors and transformers (here referred to as power components) for modern AC/DC switching power supplies require magnetic materials that have high power density and efficiency at high frequencies, with high magnetic saturation, low coercivity, and multi‐micrometer thicknesses to increase magnetic energy storage and power handling. Rather than using a single‐phase magnetic material in a polymer‐based composite, a composite formed from two magnetic phases (such as a 0‐3 nanocomposite) can simultaneously achieve all of the listed requirements and benefit from contributions by both the zero‐ and three‐dimensional phases to the magnetic properties. The fabrication of 0‐3 magnetic nanocomposites for power component applications requires a method to deposit magnetic nanoparticles into thick, physically stable yet porous films, and a subsequent method for infiltrating the magnetic nanoparticle film with another magnetic material. Here, the deposition of magnetic nanoparticles into micron‐thick films using electrophoretic deposition (EPD) is discussed. This is described along with a new method, to improve upon traditional EPD methods by increasing film–substrate interactions with chelating agents, therefore increasing film stability. Next, the use of electro‐infiltration for fully incorporating a secondary magnetic material within the nanoparticle film is presented, showing the cumulative fabrication process with the addition of a multilayered nanocomposite fabrication technique for increasing overall nanocomposite thickness. The subsequent cross‐sectional and magnetic characterization of the fabricated 0‐3 nanocomposites is also shown. Finally, future directions for 0‐3 magnetic nanocomposites are offered, with emphasis on potential materials synthesis techniques and on translating knowledge beyond power component applications.

Impact of Calcium Doping of YBa2Cu3O7-δ Multilayer Thin Films on the Flux Pinning Landscape at 65–5 K, 0–9 T for Various Applications

An important research goal in the applications of high temperature superconductor YBa <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> Cu <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> O <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">7-δ</sub> (YBCO) thin films is increasing both the critical current density and also the isotropic nature of the film. YBCO is inherently anisotropic due to its layered perovskite structure. The critical current density of YBCO thin films is enhanced by increasing the flux pinning sites in the film by the addition of insulating nano-phase materials, such as BaZrO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> (BZO) nanorods, which are also anisotropic in nature. Using a multilayer pulsed laser deposition technique has been shown to produce films with inclusions that are more isotropic in nature. However, the defective BZO nanorod interface, resulting from its lattice mismatch with YBCO, prevents obtaining optimum pinning force. This research explores the effect of Ca doped YBCO space layers in the multilayer composite film, on the BZO nanorod/YBCO interface, over a wide range of conditions of 65–5 K and 0– 9T that are suitable for various applications. The interplay of combining these three variables: BaZrO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> addition to YBCO, multilayer film growth resulting from varying pulsed laser deposition conditions, and employing calcium doped YBCO space layers, and the resulting impact on film microstructures and superconducting properties, will be presented.

The Etiology, Diagnosis, and Management of Cerebrospinal Fluid Rhinorrhea: A Tertiary Center Experience.

Introduction The aim of the present study was to describe our institution's nine years of experience in the endoscopic endonasal management of cerebrospinal fluid (CSF) rhinorrhea and to discuss the causes, sites, and outcomes. Methodology The medical records of patients diagnosed with CSF rhinorrhea in King Abdulaziz Medical City-Jeddah (KAMC-J) between 2014 and 2023 were retrospectively reviewed, and all relevant information including body mass index, medical and surgical history, and postoperative outcomes were obtained. Results A total of 20 cases were included in the present study, sixteen (80%) of which were females and four (20%) were males. The mean age of participants was 42.59±13.9 years. Nine cases (45%) were spontaneous CSF rhinorrhea and 11 (55%) were traumatic; within the traumatic group, six cases (54%) were iatrogenic either following previous neurosurgery or functional endoscopic sinus surgery, while the remaining five cases were related to motor vehicle accidents. The mean body mass index for the spontaneous CSF leak was 32 Kg/m2, and 33 Kg/m2 for the traumatic leaks, no statistically significant difference was noted. The cribriform plate was the most common site of leakage (65%). A multilayer surgical technique using facia lata graft with nasoseptal flap was the most common choice for reconstruction with a first-attempt success rate approximating 90%. A recurrence was observed in two patients only. No major complications were reported. The average length of stay was nine days. Conclusion The endoscopic endonasal repair of CSF leak is a safe and reliable procedure and is associated with high success rates and low risk of complications. Therefore, it should be preferred as a first-line treatment for CSF rhinorrhea.

Does Time to Initiation of Adjuvant Radiotherapy Affect Reconstruction Outcomes after Endoscopic Resection of Skull Base Malignancies?

Introduction and Objective It is unclear if the length of the time interval to initiation of adjuvant radiation therapy (RT) after endoscopic endonasal surgery affects reconstruction outcomes. In this study we present our experience with adjuvant RT after endoscopic endonasal procedures, to determine if the time to RT after surgery impacts post-RT reconstruction complication rates. Methods A retrospective cohort study of 164 patients who underwent endoscopic endonasal surgery between 1998 and 2021 was conducted. Using Cox proportional hazard ratios (HRs), we evaluated several variables and the complications that occurred during the 1-year period after starting RT. Results Seventy-eight (47.5%) and eighty-six patients (52.5%) received RT before and after the sixth postoperative week, respectively. The overall post-RT complication rates were 28%, most of these were severe infections ( n = 20, 12.2%) and delayed CSF leak ( n = 4, 2.5%). There was no significant difference in the post-RT complications between the patients who received postoperative RT before or after the sixth operative week (HR: 1.13; 95% confidence interval: 0.63-2.02; p = 0.675 ). Univariate analysis demonstrated negative impact associated with smoking history ( p = 0.015 ), the use of neoadjuvant chemotherapy ( p = 0.0001 ), and the use of photon therapy ( p = 0.012 ); and we found a positive impact with the use of multilayer reconstruction techniques (overall, p = 0.041 ; with fat, p = 0.038 ; and/or fascia graft, p = 0.035 ). After a multivariate analysis only, smoking history was an independent risk factor for post-RT complications ( p = 0.012 ). Conclusion Delaying RT for more than 6 weeks after endoscopic endonasal surgery does not provide a significant benefit for reconstruction outcomes. However, special attention may be warranted in patients with smoking history who have received neoadjuvant chemotherapy, or in patients who will receive photon-based RT after surgery as these groups were found to have increased complication rates post-RT.

A Multilayer Approach for Intrusion Detection with Lightweight Multilayer Perceptron and LSTM Deep Learning Models

Intrusion detection is essential in the field of cybersecurity for protecting networks and computer systems from nefarious activity. We suggest a novel multilayer strategy that combines the strength of the Lightweight Multilayer Perceptron (MLP) and Long Short-Term Memory (LSTM) deep learning models in order to improve the precision and effectiveness of intrusion detection.The initial layer for extraction of features and representation is the Lightweight MLP. Its streamlined architecture allows for quick network data processing while still maintaining competitive performance. The LSTM deep learning model, which is excellent at identifying temporal correlations and patterns in sequential data, receives the extracted features after that.Our multilayer technique successfully manages the highly dimensional and dynamic nature of data from networks by merging these two models. We undertake extensive tests on benchmark datasets, and the outcomes show that our strategy performs better than conventional single-model intrusion detection techniques.The suggested multilayer method also demonstrates outstanding efficiency, which makes it particularly ideal for real-time intrusion detection in expansive network environments. Our multilayer approach offers a strong and dependable solution for identifying and reducing intrusions, strengthening the security position of computer systems and networks as cyber threats continue to advance.

Carbide evolution and its effect on the impact toughness of the 9Cr/CrMoV dissimilar welded joint during the aging treatment

The microstructure evolution in the weld metal (WM) and its effect on the impact toughness for the 9Cr/CrMoV dissimilar welded joint with various aging time was systematically investigated. With the aging time increased from 0 h to 3,000 h, the specimen aged at 470 ℃ for 1,000 h revealed the lowest impact energy (13.5 J). Moreover, the impact fracture morphology details were obtained by scanning electron microscopy (SEM). The results showed that the quasi-cleavage fracture appeared for the specimens in the original and aged (aged at 470 °C for 3,000 h) states, while the cleavage fracture could be observed for the specimen aged at 470 °C for 1,000 h. Besides, the microstructure observation exhibited that the main microstructure in the WMs for the specimens in the original and aged states were all the tempered martensite. The columnar and equiaxed grain zones formed owing to the multi-layer and multi-pass techniques. Based on the characterization analysis of the precipitates for the aged specimens, the coarsening of the carbides was determined as the crucial factors to decrease the impact energy. On the contrary, with the aging time increased, the newly precipitated fine carbides could produce the positive effects on the impact toughness. In the original state, the impact energy of the specimens was about 29.2 J. With the aging time increased to 1,000 h and 3,000 h, the impact energy became 13.5 J and 21.0 J, respectively.

A new process to develop marine natural gas hydrate with thermal stimulation and high-efficiency sand control

The development of marine gas hydrate from low-permeability offshore reservoirs with serious sand incursion issues is a challenging task. Currently, there are no mature technologies in the world. Therefore, we proposed a comprehensive development process, including the following measures: (1) Vertical injection-production well pattern enhanced by multi-layer fracturing and hot water injection by seawater source heat pump. (2) An advanced multi-layer hydraulic fracturing technique incorporating cold fracturing fluid, low-temperature consolidation proppant, multi-stage sliding sleeve packer, and a chemical diverting agent. (3) A series of sand control measures including hydraulic fracturing, consolidation proppant, and stand-alone screen. (4) Several rounds of hot water injection-soaking-production (huff-n-puff) on injection wells, and finally continuous injection-production, with depressurization. Then, we built a gas hydrate decomposition rate model to simulate this process. The results show that hot water injection combined with multi-layer hydraulic fracturing can significantly improve the gas hydrate dissociation rate compared with the schemes without hot water injection or fracturing. Combining hot water injection by seawater source heat pump, multi-layer horizontal fractures by advanced hydraulic fracturing technique, and a set of sand control techniques, can efficiently control sand while producing gas hydrate.

Plastic Surgery Closure of Complex Spinal Wounds.

Wound breakdown and infection are common complications after complex spine surgery and may occur in up to 40% of high-risk patients. These are challenging scenarios which can result in a prolonged hospital stay, revision surgery, and elevated costs. Reconstructive specialists can do prophylactic closures for high-risk groups to potentially reduce the risk of developing a wound complication. These plastic surgery techniques often involve multilayered closure, with the addition of local muscle and/or fasciocutaneous flaps. The goal of this study was to review the literature for risks associated with wound complications, identification of high-risk patients, and the advantages of using plastic surgery techniques. In addition, we elaborate on the multilayered and flap closure technique for complex spine surgery which is done at our institution.

Creation of wildfire susceptibility maps in the Mediterranean Region (Turkey) using convolutional neural networks and multilayer perceptron techniques

Considering the natural disasters that have developed in the world in recent years, it is known that there is an increase in wildfire disasters with the effects of climate change. In this study, wildfire susceptible areas were determined in the provinces of Muğla, Antalya, Mersin, Adana, Osmaniye, and Hatay in the Mediterranean region (Turkey). Within the scope of this purpose, Convolutional Neural Network (CNN) and Multilayer Perceptron (MLP) methods, the most widely used deep learning techniques in the literature in recent years, were preferred to create Wildfire susceptibility models. Seventeen environmental variables were used in the analyses, and these variables were grouped as topographic factors, anthropological and environmental factors, climatic factors, and vegetation factors. In addition, the number of fire inventory data has been balanced with the help of the Synthetic Minority Oversampling Technique (SMOTE) used to increase the model result performance of the scarce inventory data. In the maps obtained by CNN and MLP methods, 17% and 28% of the study area were determined as high and very high susceptible areas, respectively. The results demonstrated that the CNN model had superior performance in Wildfire susceptibility assessment with accuracy (%85.8), precision (%98.7), sensitivity (%85.5), F- Score (%91.6), and ROC curve (%78.6). This model was followed by the MLP model with slightly lower accuracy values, which indicates that the CNN models can reach considerably better prediction capability than the MLP models. Finally, the wildfire susceptibility maps produced by deep learning methods could aid decision-makers and government organizations in the Mediterranean region in preventing future natural disasters.

Moiré modulation of lattice strains in PdTe2 quantum Films

We report the epitaxial growth of PdTe2 ultrathin films on a topological insulator Bi2Se3. A prominent moiré pattern was observed in scanning tunneling microscope measurements. The moiré periodicity increases as film thickness decreases, indicating a lattice expansion of epitaxial PdTe2 thin films at lower thicknesses. In addition, our simulations based on a multilayer relaxation technique reveal uniaxial lattice strains at the edge of PdTe2 domains, and anisotropic strain distributions throughout the moiré supercell with a net change in lattice strain up to ∼2.9%. Our density functional theory calculations show that this strain effect leads to a narrowing of the band gap at Γ point near the Fermi level. Under a strain of ∼2.8%, the band gap at Γ closes completely. Further increasing the lattice strain makes the band gap reopen and the order of conduction band and valence bands inverted in energy. The experimental and theoretical results shed light on a method for constructing quantum grids of topological band structure under the modulation of moiré potentials.

Detection of Human Protein Structures by Select Deep Learning Models and Dynamic Systems

Peptide bonds bind amino acids together to form proteins. Because of the way amino acids fold, proteins have a three-dimensional structure. Increased data, or samples, improves machine learning models that learn from examples. ANNs, a single-layer learning system, require sophisticated systems and time to learn massive volumes of data over time. Today, the multi-layer deep learning technique is preferred. Deep learning uses artificial neural networks. This part of the work provides technical details about the deep learning methods used. This research's deep learning methods include CNN, Hidden Markov Model (HMM), Recurrent Weighted Average (RWA), and Conditional Random Fields (CRF). The training and testing results of these models are presented in this work. For this work, the CNN, HMM, RWA, and CRF algorithms were all compared using the CB513 dataset. In addition, each method was analyzed and contrasted with other research conducted previously. In this particular research endeavour, the respective success rates of the four models that were built for predicting the protein secondary structure were as follows: 82.54%, 81.06%, 81.10%, and 81.48%. The models and working environment produced in this study can be used to predict protein secondary structure quickly. In deep learning experiments, data amount affects learning. Increasing data will test the study's models&#x0D;

Multi-layered repair of high-flow CSF fistulae following endoscopic skull base surgery without nasal packing or lumbar drains: technical refinements to optimise outcome.

Post-operative CSF leak remains a significant problem following endoscopic skull base surgery, particularly when there is a high-flow intra-operative CSF leak. Most skull base repair techniques are accompanied by the insertion of a lumbar drain and/or the use of nasal packing which have significant shortcomings. Our aim was to review the results of a large series of endoscopic skull base cases where a high-flow intra-operative CSF leak rate was encountered and repaired to assess if modifications in technique could reduce the post-operative CSF leak rate. A retrospective review of a prospectively maintained database of skull base cases performed by a single surgeon over a 10-year period was performed. Data regarding patient demographics, underlying pathology, skull base repair techniques and post-operative complications were analysed. One hundred forty-two cases with high-flow intra-operative CSF leak were included in the study. The most common pathologies were craniopharyngiomas (55/142, 39%), pituitary adenomas (34/142, 24%) and meningiomas (24/142, 17%). The CSF leak rate was 7/36 (19%) when a non-standardised skull base repair technique was used. However, with the adoption of a standardised, multi-layer repair technique, the post-operative CSF leak rate decreased significantly (4/106, 4% vs. 7/36, 19%, p = 0.006). This improvement in the rate of post-operative CSF leak was achieved without nasal packing or lumbar drains. With iterative modifications to a multi-layered closure technique for high-flow intra-operative CSF leaks, it is possible to obtain a very low rate of post-operative CSF leak, without lumbar drains or nasal packing.