Hybrid Technique Research Articles

Multiplexed spatial transcriptomics methods and the application of expansion microscopy

While spatial transcriptomics has undeniably revolutionized our ability to study cellular organization, it has driven the development of a great number of innovative transcriptomics methods, which can be classified into in situ sequencing (ISS) methods, in situ hybridization (ISH) techniques, and next-generation sequencing (NGS)-based sequencing with region capture. These technologies not only refine our understanding of cellular processes, but also open up new possibilities for breakthroughs in various research domains. One challenge of spatial transcriptomics experiments is the limitation of RNA detection due to optical crowding of RNA in the cells. Expansion microscopy (ExM), characterized by the controlled enlargement of biological specimens, offers a means to achieve super-resolution imaging, overcoming the diffraction limit inherent in conventional microscopy and enabling precise visualization of RNA in spatial transcriptomics methods. In this review, we elaborate on ISS, ISH and NGS-based spatial transcriptomic protocols and on how performance of these techniques can be extended by the combination of these protocols with ExM. Moving beyond the techniques and procedures, we highlight the broader implications of transcriptomics in biology and medicine. These include valuable insight into the spatial organization of gene expression in cells within tissues, aid in the identification and the distinction of cell types and subpopulations and understanding of molecular mechanisms and intercellular changes driving disease development.

In situ imaging of intracellular miRNAs in tumour cells by branched hybridisation chain reaction.

The ability to visualise microRNA in situ is crucial for studying microRNAs, their microRNA-associated biological functions and disease diagnosis. Traditional fluorescence in situ hybridisation methods based on paraformaldehyde fixation of microRNAs suffer from release of microRNAs from cells, which limits the sensitivity of in situ hybridisation, making them unsuitable for the detection of small, low-abundance microRNAs. To reduce the loss, microRNAs were covalently cross-linked to proteins within cells by combining EDC and paraformaldehyde, and the target microRNA was used as the initiator chain for a branched hybridisation chain reaction to detect microRNA expression levels in situ. A simplified branched hybridisation chain reaction can be realised by coupling two hybridisation chain reaction circuits with a hairpin linker. Upon forming the primary hybridisation chain reaction product with extended sequence, this sequence reacts with the linker hairpin H3 to release the initiator sequence, resulting in the formation of numerous dendritic branched hybridisation chain reaction products. Imaging results show that this technique can detect microRNAs with high sensitivity and selectivity at both the single-cell and single-molecule levels. Compared with the traditional fluorescence in situ hybridisation technique, this method greatly improves the sensitivity and image resolution of in situ imaging detection. Therefore, we believe that the target-initiated branched hybridisation chain reaction based in situ detection method provides a reliable assay platform for analysing disease-related microRNA expression.

Bidirectional Power Sharing Control with Current-Fed Dual Active Bridge Converter: Hybrid Technique

This paper proposes a hybrid method for controlling bidirectional power sharing among grids and dc microgrids. The interlinking converter (IC) and current-fed dual active bridge (CFDAB) converters connect the grid and dc microgrid. The proposed approach is the joint implementation of golden eagle optimization and radial basis function neural network, hence, named the GEO-RBFNN approach. The bidirectional power distribution control signal analysis significantly diminishes power distribution deviation and circulating current. This power-sharing control system neglects the need for battery backup since the required amount of power is brought from or handled by an AC utility. The dc microgrid incorporates the dc to dc converter, from which boost converters use sources and buckconverters use supply loads. The control of bidirectional power sharing among the microgrids and the grid is attained with the aid of the GEO-RBFNN algorithm. It delivers certain aids, like higher predictability, highly reliable results, high speed, and less complexity. The outcome is investigated on the MATLAB platform. According to the comparison outcome, the proposed method delivers higher performance than the existing system. The proposed method gives higher comparison outcomes than the current methods, which can conquer the associated problems. The proposed method-based settling time is 3.356 ms, and the rise time is 1.555 ms. The efficiency based on the proposed method is 97.54%, which is higher than the existing methods.

A Hybrid RBFNN-SPOA Technique for Multi-Source EV Power System with Single-Switch DC-DC Converter

With a single-switched DC-DC converter, a hybrid approach is proposed for a fast-charging (FC) dc to dc converter with the controller for an electric vehicle charging station (EVCS) that combines solar photovoltaic (PV), fuel cells (FC), and a battery energy storage system (BESS). The proposed hybrid technique integrates a radial-basis-function-neural-network (RBFNN) and a student-psychology-optimization-algorithm (SPOA); commonly known as the RBFNN-SPOA technique. The PV-FC hybrid electric vehicle systems, like controllers, electric vehicle, and the vehicle’s power source, are displayed. The proposed converter architectures have less voltage waveform changes, a low voltage stress on semiconductor power sources, and a high-voltage ratio of conversion. The proposed method is to use FC successfully at battery charge states and varied radiation levels. The FC in the controller of SPOA may change the inputs and outputs depending on the battery state of charge (SoC) and PV irradiation. Similarly, the needed input-torque for the motor is forecasted by the recalling recurrent neural network controller using several manually produced torque signals. The performance of the proposed technique is evaluated in MATLAB and is compared to ant colony optimization (ACO), crow optimization algorithm (COA), and fuzzy logic controller (FLC) approaches. According to the results, the efficiency of the proposed technique is 99.17%.

Unravelling the unusual: chromosome elimination, nondisjunction and extra pollen mitosis characterize the Bchromosome in wild sorghum.

The B chromosomes exhibit diverse behaviour compared with conventional genetic models. The capacity of the B chromosome either to accumulate or to be eliminated in a tissue-specific manner is dependent on biological processes related to aberrant cell division(s), but here yet remains compatible with normal development. We studied B chromosome elimination in Sorghum purpureosericeum embryos through cryo-sections and demonstrated the B chromosome instability during plant growth using flow cytometry, molecular markers and fluorescent in situ hybridization techniques. Consequently, using B chromosome-specific probes we revealed the non-Mendelian inheritance of B chromosomes in developing pollen. We disclosed that the occurrence of the B chromosome is specific to certain tissues or organs. The distribution pattern is mainly caused by an extensive elimination that functions primarily during embryo development and persists throughout plant development. Furthermore, we described that B chromosome accumulation can occur either by nondisjunction at first pollen mitosis (PMI) or the initiation of extra nuclear division(s) during pollen development. Our study demonstrates the existence of a not-yet-fully described B chromosome drive process, which is likely under the control of the B chromosome.

Hybrid Quantum-Dot Cellular Automata Nanocomputing Circuits

Quantum-dot cellular automata (QCA) is an emerging transistor-less field-coupled nanocomputing (FCN) approach to ultra-scale ‘nanochip’ integration. In QCA, to represent digital circuitry, electrostatic repulsion between electrons and the mechanism of electron tunnelling in quantum dots are used. QCA technology can surpass conventional complementary metal oxide semiconductor (CMOS) technology in terms of clock speed, reduced occupied chip area, and energy efficiency. To develop QCA circuits, irreversible majority gates are typically used as the primary components. Recently, some studies have introduced reversible design techniques, using reversible majority gates as the main building block, to develop ultra-energy-efficient QCA circuits. However, this approach resulted in time delays, an increase in the number of QCA cells used, and an increase in the chip area occupied. This work introduces a novel hybrid design strategy employing irreversible, reversible, and partially reversible QCA gates to establish an optimal balance between power consumption, delay time, and occupied area. This hybrid technique allows the designer to have more control over the circuit characteristics to meet different system needs. A combination of reversible, irreversible, and innovative partially reversible majority gates is used in the proposed hybrid design method. We evaluated the hybrid design method by examining the half-adder circuit as a case study. We developed four hybrid QCA half-adder circuits, each of which simultaneously incorporates various types of majority gates. The QCADesigner-E 2.2 simulation tool was used to simulate the performance and energy efficiency of the half-adders. This tool provides numerical results for the circuit input/output response and heat dissipation at the physical level within a microscopic quantum mechanical model.

Alternative Hybrid Technique of Intubation Using C-MAC and Yankauer Suction Catheter: Case of A Floppy Supraglottic Mass.

Supraglottic masses can be an anaesthesiologist's nightmare due to the difficult airway scenario and bleeding risk during airway manipulation. Awake fibreoptic intubation is the primary method to secure the airway in such cases. However, most practising anaesthesiologists are not experts at handling the fibreoptic scope, especially in cases with a floppy supraglottic mass where it becomes difficult to displace the mask with the thin flexible bronchoscope. A hybrid technique of intubation in supraglottic masses using Bonfils rigid scope and C-MAC is often described but frequently not available. Here we describe a case of an elderly patient in their 80s presenting with a floppy supraglottic mass where an awake fibreoptic bronchoscope failed to secure the airway. Without access to a rigid Bonfils scope, we intuitively used a C-MAC to visualize the larynx and a yankauer suction catheter to displace the mass and perform a bougie-guided endotracheal intubation.

Arctic tern-optimized weighted feature regression system for predicting bridge scour depth

This paper presents a pioneering artificial intelligence (AI) solution – the Arctic Tern-Optimized Weighted Feature Least Squares Support Vector Regression (ATO-WFLSSVR) system to aid civil engineers in accurately predicting scour depth at bridges. This prediction system amalgamates the strengths of hybrid models by uniting a metaheuristic optimization algorithm with weighted features and least squares support vector regression (WFLSSVR). The metaheuristic algorithm concurrently optimizes all hyperparameters of constituent WFLSSVR models, resulting in a highly effective system. Validation involves a comprehensive assessment using two case studies, which include datasets of scour depths across various complexities and pier foundation types. Comparative analyses against single AI models, conventional ensemble models, hybrid techniques, and empirical methods demonstrate that ATO-WFLSSVR's reliability outperforms others in performance evaluation metrics. Specifically, for the field dataset, ATO-WFLSSVR achieves MAPE and R values of 20.92% and 0.9435, respectively, and for scour depth data at complex pier foundations, it records MAPE and R values of 6.49% and 0.9384, respectively. The automated predictive analytics underscore the robustness, efficiency, and stability of ATO-WFLSSVR compared to existing methods. This study's notable contributions include the development of an innovative optimization algorithm named Arctic Terns Optimizer (ATO), proficiency in solving high-dimensional optimization problems, and the creation of a user-friendly graphical interface system, a promising tool for civil engineers to estimate scour depth at bridges. Further testing and evaluation of ATO-WFLSSVR across diverse datasets encompassing more complex scenarios are recommended. The data and source code for this study are currently accessible at https://www.researchgate.net/profile/Jui-Sheng-Chou/publications.

UPQC-Based Hybrid Technique to Reduce Power Quality Problems in the Photovoltaic Grid System

In addition to Power Quality (PQ) problems caused by solid state devices in the distribution side of grid connected Photo Voltaic (PV) system, quality of power also suffers in the source side by the usage of converters. Generally, PQ problems mitigation strategy has turned into a critical issue in grid-connected PV systems. This paper proposes a control topology for PQ issues mitigation scheme in grid connected PV systems. The primary goal of this study is to enhance the PQ in power distribution system through eradicating the voltage interruption, voltage swell and sag as well as voltage fluctuation. To accomplish these changes, Unified Power Quality Conditioners (UPQCs) with controllers were utilized. Then the faults are mitigated by the utilization of UPQC with Tree Seeds Algorithm (TSA) — Adaptive Neuro-Fuzzy Interference System (ANFIS). At first, the normal properties of the grid-connected PV systems are dissected. From that point forward, a few interruptions are made in the system and the abnormal characteristics are analyzed. Then the abnormal characteristics of PQ problems are diminished in the utilization of UPQC and TSA–ANFIS controllers. UPQC is one of the best filters topologies which can mitigate and control all PQ problems. The combined algorithms of TSA-ANFIS are used to keep the dc-link voltage in UPQC at consistent level. The proposed hybrid approach is executed in MATLAB/Simulink platform and the performance is studied. Further, the proposed method is compared with existing Elephant Herding Optimization (EHO) technique and also with hybrid EHO-ANFIS techniques. The comparison results showed that the proposed technique is superior to the EHO and EHO-ANFIS techniques.

A hybrid multi-agent metaheuristic for the offshore wind farm cable routing problem

A crucial task concerning offshore wind farm designs is connecting previously placed turbines to a substation, such that the total cable cost is minimal. An NP-hard optimization problem named Wind Farm Cable Routing Problem (WFCRP) models this task. Previous studies have proposed Mixed Integer Linear Programming formulations (MILP) and metaheuristics for the WFCRP. However, they faced difficulties in solving instances with many turbines. Hybridization is a widely-explored approach that has produced better solutions as it combines the best features of individual algorithms. This paper proposes a hybrid algorithm for the WFCRP that combines four state-of-the-art metaheuristics and a MILP formulation. The hybridization technique uses multi-agent and Particle Swarm Optimization concepts, where particles are cooperative agents that work together to find high-quality solutions. Experimental results on instances with up to 120 turbines show that the proposed hybrid algorithm outperforms the best algorithm from the WFCRP literature.

Investigating the Effect of Class Balancing Methods on the Performance of Machine Learning Techniques: Credit Risk Application

Credit risk arises as a result of the failure of the loans given by banks to the customers to fulfill their obligations at the end of the specified term. Technological advances allow the use of machine learning methods in various sectors. These methods aim to facilitate the identification of customers at risk with the system adapted to the creditworthiness processes of banks. For this purpose, in order to make the most appropriate evaluation in the lending process of banks, re-sampling techniques to eliminate the problem of class imbalance encountered in unbalanced data sets were made balanced and their effects on machine learning were investigated. During the implementation phase, German, Australian and HMEQ credit data sets were used. Different machine learning classification methods such as Logistic Regression (LR), K-Narest Neighbor (KNN), Naive Bayes (NB), Support Vector Machines (SVM), Multilayer Perceptron (MLP), Decision Trees (DT), Random Forests (RF), Gradient Boosting Decision Trees (GBDT), Extremely Randomized Trees, Hard and Soft Voting were used to detect risky customers. The problem of class imbalance was balanced with resampling and hybrid techniques such as Random Oversampling (ROS), Random Undersampling (RUS), Balanced Bagging Classifier (BBC), SMOTE-Tomek Links and SMOTE-ENN. In this context, the performances of three different data sets were examined in four different scenarios. As a result of the study, the hybrid method, in which oversampling and undersampling methods are used together for the class balancing problem, showed the best classification performance among machine learning techniques.

Predictive Placement of IC Chips using ANN-GA Approach for Efficient Thermal Cooling

In this research, numerical modelling is used to explore the heat transfer through natural convection capabilities of nine aluminum integrated circuit chips that are installed on substrate board. The goal is to figure out where on the substrate board these IC chips would be best placed if they were arranged differently. The dimensionless parameter (λ) plays a very essential role, and by applying a hybrid technique consisting of ANN and GA. ANSYS Icepack calculates IC chip temperature distributions in 3D steady state numerical simulations. It has been shown that the form, dimensions, and IC chips' substrate board positioning affects their operating temperature. In comparison to the strategies that have been used in the past, hybrid optimization is the strategy that has shown to be the most reliable in properly predicting how the IC chips would be arranged on the substrate board. It has been observed that higher values of one of these parameters lead to a reduction in the maximum temperature surplus. A correlation has been established to illustrate this relationship as it increases. The most favorable simulation outcomes are utilized to drive a genetic algorithm (GA), which identifies the optimal configuration ensuring that the temperatures of the heat sources remain well below their specified maximum operating conditions, as outlined in the data sheets. The maximum temperature variation between the lowest and highest extreme configurations ranges between 4 - 8%. The smallest size IC chip, U2 with high heat dissipation rate attains the maximum temperature in the configuration, however, the temperature variation for the low powered IC chips U3, U4 and U7 are very small. Found good agreement of both the data with an error band of 10%, and thus confirms the accuracy of the network.

Outcome of Flexible Intramedullary Nailing versus Plating in Treatment of Diaphyseal Femur Fractures in Paediatrics: Systematic Review and Meta-analysis

Abstract Background Pediatric femoral fractures are the most the common long bone fracture in children, with one third of these occurring between ages 5 to 12. These injuries are usually the result of road traffic accidents, sports and non-accidental injury. Different modalities exist for managing these fractures, often stratified according to the age of the patient. Aim of the Work The aim of this work is to provide a complete overview of the optimal surgical treatment of diaphyseal femur fractures in children by evaluating and comparing the clinical and functional outcomes of flexible intramedullary nailing versus plating for such fractures. Patients and Methods This review followed the Cochrane Handbook's standard methodology and reported the findings in accordance with the Preferred Reporting Items for Systematic Reviews and Meta- analyses (PRISMA) statement guidelines. Result In patients undergoing flexible nailing, the surgical variable data found this treatment modality to be superior in terms of certain operative features: shorter operative duration times (p = 0.00001), smaller volumes of estimated blood loss (p = 0.00001). There was no difference regarding length of hostital stay (p = 0.59). This suggests that flexible nailing may offer increased safety to patients in terms of duration of anesthesia, volume of blood loss, and cost of surgery when compared to plating. However, Secondary outcome analysis also found a statistically significant increased risk of malunion (p = 0.002) and metalwork irritation (p = 0.00001) when using FIN compared to plating techniques. There was no difference regarding risk of infection (p = 0.53) and developing leg length discrepancy (p = 0.44). Conclusion Options for stabilization and fixation in this age group include flexible nailing, plating (open or sub-muscular), external fixation, or hybrid techniques.

Multiplexed in situ hybridization reveals distinct lineage identities for major and minor vein initiation during maize leaf development

Leaves of flowering plants are characterized by diverse venation patterns. Patterning begins with the selection of vein-forming procambial initial cells from within the ground meristem of a developing leaf, a process which is considered to be auxin-dependent, and continues until veins are anatomically differentiated with functional xylem and phloem. At present, the mechanisms responsible for leaf venation patterning are primarily characterized in the model eudicot Arabidopsis thaliana which displays a reticulate venation network. However, evidence suggests that vein development may proceed via a different mechanism in monocot leaves where venation patterning is parallel. Here, we employed Molecular Cartography, a multiplexed in situ hybridization technique, to analyze the spatiotemporal localization of a subset of auxin-related genes and candidate regulators of vein patterning in maize leaves. We show how different combinations of auxin influx and efflux transporters are recruited during leaf and vein specification and how major and minor vein ranks develop with distinct identities. The localization of the procambial marker PIN1a and the spatial arrangement of procambial initial cells that give rise to major and minor vein ranks further suggests that vein spacing is prepatterned across the medio-lateral leaf axis prior to accumulation of the PIN1a auxin transporter. In contrast, patterning in the adaxial-abaxial axis occurs progressively, with markers of xylem and phloem gradually becoming polarized as differentiation proceeds. Collectively, our data suggest that both lineage- and position-based mechanisms may underpin vein patterning in maize leaves.

Insights into brain tumor diagnosis: exploring in situ hybridization techniques.

Diagnosing brain tumors is critical due to their complex nature. This review explores the potential of in situ hybridization for diagnosing brain neoplasms, examining their attributes and applications in neurology and oncology. The review surveys literature and cross-references findings with the OMIM database, examining 513 records. It pinpoints mutations suitable for in situ hybridization and identifies common chromosomal and gene anomalies in brain tumors. Emphasis is placed on mutations' clinical implications, including prognosis and drug sensitivity. Amplifications in EGFR, MDM2, and MDM4, along with Y chromosome loss, chromosome 7 polysomy, and deletions of PTEN, CDKN2/p16, TP53, and DMBT1, correlate with poor prognosis in glioma patients. Protective genetic changes in glioma include increased expression of ADGRB3/1, IL12B, DYRKA1, VEGFC, LRRC4, and BMP4. Elevated MMP24 expression worsens prognosis in glioma, oligodendroglioma, and meningioma patients. Meningioma exhibits common chromosomal anomalies like loss of chromosomes 1, 9, 17, and 22, with specific genes implicated in their development. Main occurrences in medulloblastoma include the formation of isochromosome 17q and SHH signaling pathway disruption. Increased expression of BARHL1 is associated with prolonged survival. Adenomas mutations were reviewed with a focus on adenoma-carcinoma transition and different subtypes, with MMP9 identified as the main metalloprotease implicated in tumor progression. Molecular-genetic diagnostics for common brain tumors involve diverse genetic anomalies. In situ hybridization shows promise for diagnosing and prognosticating tumors. Detecting tumor-specific alterations is vital for prognosis and treatment. However, many mutations require other methods, hindering in situ hybridization from becoming the primary diagnostic method.

Management Of The Pediatric Difficult Airway: New Strategies Unveiled

Abstract Purpose of Review This article outlines recent advancements in pediatric difficult airway management, driven by collaborative research and technology. It highlights challenges in newborns and infants, emphasizing initiatives like the Pediatric Difficult Intubation Registry (PeDI-R) and large-scale observational studies like APRICOT and NECTARINE. These endeavors aim to refine management strategies, enhancing approaches to both anticipated and unforeseen difficult pediatric airways. Recent Findings Studies have elucidated various facets of pediatric airway management, including difficult intubation incidence, contributing factors and efficacy of diverse techniques and devices. Noteworthy advancements include videolaryngoscopy, hybrid techniques, passive oxygenation, sedation, and muscle relaxation with a focus on reducing intubation attempts. Additionally, ultrasound’s utility and the significance of extubation planning are highlighted. Summary To summarize, continued research and collaboration refine strategies for difficult pediatric airway management, striving to enhance patient outcomes and safety through dissemination of knowledge and leveraging recent insights.

Cytogenetic analysis of meiotic behaviour and stability in a trigeneric hybrid (triticale x trigopiro).

Trigeneric hybrids in Triticeae may help to establish evolutionary relationships among different genomes present in the same cellular genetic background and to transfer different alien characters into cultivated wheat. In the present study, a trigeneric hybrid involving species of Triticum, Secale, and Thinopyrum was synthesized by crossing hexaploid triticale with hexaploid trigopiro. The meiotic behaviour of chromosomes belonging to different genomes was analyzed, using routine and in situ hybridization techniques in F1, F2, and F3 generations of the trigeneric hybrid. The purpose of this study was to determine the chromosome number and genomic constitution and to discuss the mechanisms involved in the stabilization of the artificial tricepiro hybrids. The chromosome number of the trigeneric F1 hybrid was 2n = 42. Between 12 and 16 bivalents were observed in the central zone of the equatorial meiotic plate and between 9 and 18 univalents were found in the periphery of the MI equatorial plate. Seven of these univalents showed hybridization signals with rye DNA. Lagging rye and non-rye chromosomes and separation of sister chromatids were found in anaphase I. Tetrads with a maximum of six micronuclei, with and without hybridization signals of rye DNA, were observed. After three generations, meiotic cells revealed the presence of 42 chromosomes and 21 bivalents in diakinesis cells. The presence of 14 rye (Secale cereale) chromosomes and the complete pairing of chromosomes in F3 hybrids suggest that rye chromosomes would be preferentially transmitted to the progeny and that an elimination mechanism would act on chromosomes of Thinopyrum and wheat D genome.

A novel experimental method for determination of forming limits with generalized non-planar stress state using hydro-assisted incremental forming

Several studies have explored analytically predicting forming limits in processes like hydroforming and incremental forming, yet there’s a lack of discussion on effective experimental methods. This paper introduces hydro-assisted incremental forming (HAIF) as a hybrid technique combining incremental forming and hydromechanical deep drawing, resulting in improved formability through simultaneous application of normal and through-thickness stresses. A novel test method is devised based on this process, and forming limits are assessed through both experimental and finite element approaches. The authors' earlier analytical forming limit predictions are scrutinized using experimental tests and simulations, revealing a good match. The study reaffirms that the application of normal and through-thickness stresses enhances formability across various strain paths, especially in plane strain mode.

Exploring Hybrid Techniques for Enhanced Pitch Estimation in Speech Processing

aims: 1. To develop a hybrid approach combining the Pitch Estimation Filter (PEF) and Cepstrum Pitch Determination (CPD) methods for pitch detection in audio signals. 2. To conduct comparative analysis with existing pitch detection methodologies, including Normalized Correlation Function (NCF), Pitch Estimation Filter (PEF), Log-Harmonic Summation (LHS), Summation of Residual Harmonics (SRH) and Cepstrum Pitch Determination (CEP), to assess the performance and accuracy of the proposed hybrid approach. 3. To evaluate the effectiveness of the hybrid approach in various real-world applications such as speech recognition and music transcription, using performance metrics including Gross Pitch Error (GPE) and classification accuracy through a K-Nearest Neighbors (KNN) classifier. background: The study discussed the difficulties in assessing pitch detection algorithms in real-world applications, especially when it comes to audio synthesis and music production. Prominent performance metrics and criteria pertinent to pitch tracking in interactive music applications were identified by the authors through comprehensive user studies and surveys with audio engineers and professional musicians. The results demonstrated the need for user-centered design approaches in algorithm development and evaluation by emphasizing the significance of taking user preferences and practical requirements into account when evaluating the effectiveness of pitch detection algorithms. objective: 1. To develop a hybrid approach combining the Pitch Estimation Filter (PEF) and Cepstrum Pitch Determination (CPD) methods for pitch detection in audio signals. 2. To conduct comparative analysis with existing pitch detection methodologies, including Normalized Correlation Function (NCF), Pitch Estimation Filter (PEF), Log-Harmonic Summation (LHS), Summation of Residual Harmonics (SRH) and Cepstrum Pitch Determination (CEP), to assess the performance and accuracy of the proposed hybrid approach. 3. To evaluate the effectiveness of the hybrid approach in various real-world applications such as speech recognition and music transcription, using performance metrics including Gross Pitch Error (GPE) and classification accuracy through a K-Nearest Neighbors (KNN) classifier. method: Proposed PEF+CEP result: Finally, a comparison and analysis of different pitch detection techniques revealed how well they performed in terms of important evaluation metrics like accuracy, specificity, sensitivity, and gross pitch error (GPE). Conventional methods such as Normalized Correlation Function (NCF), Pitch Estimation Filter (PEF), Log-Harmonic Summation (LHS), Summation of Residual Harmonics(SRH) and Cepstrum Pitch Determination (CEP) perform admirably in terms of specificity and accuracy, but they are not very effective in terms of sensitivity and GPE. On the other hand, the suggested hybrid approach, Proposed PEF+CEP, offers a noteworthy enhancement in accuracy, attaining a remarkable 98.8%, in addition to a sensitivity of 99.2%. The hybrid approach exhibits a slightly higher GPE than some traditional methods, but these minor deviations are outweighed by the significant improvements in accuracy and sensitivity that it offers. Furthermore, the Proposed PEF+CEP method is a promising solution for reliable and accurate pitch detection in speech processing applications because it strikes a strong balance between computational efficiency, training time, model size, and convergence rate. The suggested method offers notable improvements in pitch detection accuracy and reliability while addressing the drawbacks of separate approaches by utilizing the advantages of both PEF and CEP techniques. As a result, the suggested PEF+CEP approach stands out as a significant advancement in speech processing, offering enhanced functionality and versatility in a range of real-world settings. conclusion: Finally, a comparison and analysis of different pitch detection techniques revealed how well they performed in terms of important evaluation metrics like accuracy, specificity, sensitivity, and gross pitch error (GPE). Conventional methods such as Normalized Correlation Function (NCF), Pitch Estimation Filter (PEF), Log-Harmonic Summation (LHS), Summation of Residual Harmonics(SRH) and Cepstrum Pitch Determination (CEP) perform admirably in terms of specificity and accuracy, but they are not very effective in terms of sensitivity and GPE. On the other hand, the suggested hybrid approach, Proposed PEF+CEP, offers a noteworthy enhancement in accuracy, attaining a remarkable 98.8%, in addition to a sensitivity of 99.2%. The hybrid approach exhibits a slightly higher GPE than some traditional methods, but these minor deviations are outweighed by the significant improvements in accuracy and sensitivity that it offers. Furthermore, the Proposed PEF+CEP method is a promising solution for reliable and accurate pitch detection in speech processing applications because it strikes a strong balance between computational efficiency, training time, model size, and convergence rate. The suggested method offers notable improvements in pitch detection accuracy and reliability while addressing the drawbacks of separate approaches by utilizing the advantages of both PEF and CEP techniques. As a result, the suggested PEF+CEP approach stands out as a significant advancement in speech processing, offering enhanced functionality and versatility in a range of real-world settings. Pitch detection algorithms could become even more complex and effective with more research and development in this area, enabling improvements in text-to-speech synthesis, speaker Identification, And Speech Recognition, Among Other Fields. other: Nil

Personalized total knee arthroplasty in patients with extra-articular deformities.

Over the years, with a better understanding of knee anatomy and biomechanics, superior implant designs, advanced surgical techniques, and the availability of precision tools such as robotics and navigation, a more personalized approach to total knee arthroplasty (TKA) has emerged. In the presence of extra-articular deformities, performing personalized TKA can be more challenging and specific considerations are required, since one has to deal with an acquired pathological anatomy. Performing personalized TKA surgery in patients with extra-articular deformities, the surgeon can: (1) resurface the joint, omitting the extra-articular deformity; (2) partially compensate the extra-articular deformity with intra-articular correction (hybrid technique), or (3) correct the extra-articular deformity combined with a joint resurfacing TKA (single stage or two-stage procedure). Omitting the acquired lower limb malalignment by resurfacing the knee has the advantages of respecting the joint surface anatomy and preserving soft tissue laxities. On the other hand, it maintains pathological joint load and lower limb kinematics with potentially detrimental outcomes. The hybrid technique can be performed in most cases. It circumvents complications associated with osteotomies and brings lower limb axes closer to native alignment. On the other hand, it creates some intra-articular imbalances, which may require soft tissue releases and/or constrained implants. Correcting the extra-articular deformity (through an osteotomy) in conjunction with joint resurfacing TKA represents the only true kinematic alignment technique, as it aims to reproduce native knee laxity and overall lower limb axis.